- 3491617597
- IMT Lucca, Laboratory of innovation management and economics, Department MemberUniversity of Salerno, Department of Economics and Statistics, Faculty Member, and 3 moreadd
- Spatial econometrics, Panel Data, Gravity Model, Spatial Filtering, International Trade, Trade Costs, and 35 moreSocial Networks, Patents, Migration, Gravity Model in International Trade, Economics, International Economics, Econometrics, Spatial Analysis, Applied Econometrics, Economics of Innovation, Regional Economics, Regional Science, Spatial Economics, Mapping, Data Visualization, Geolocation, Ethnic Conflict and Civil War, Water Scarcity and Conflict, International Migration, Spatial Modeling, Migration Studies, Spatial Statistics, Social Network Analysis (SNA), Sport, Sports Statistics, Sport Science, Data Mining, Sports Mathematics, Peace and Conflict Studies, High Dimensional Data, Logistic Regression, Variable Selection, Mobile Phones, Matrix Completion, and Functional data analysisedit
- We are hiring! Comunico con piacere che è stato bandito un assegno di ricerca 12 mesi (rinnovabile) in SECS-S/02 pre... moreWe are hiring!
Comunico con piacere che è stato bandito un assegno di ricerca 12 mesi (rinnovabile) in SECS-S/02 presso l’Università di Bergamo e nell’ambito del Progetto PRIN/PNRR 2022 “SIGNUM: Study of mobile phone siGNals for the evalUation of the interconnections between Mobility and the environment in Lombardia”, di cui trovate maggiori dettagli qui: https://lnkd.in/dd9VPF9A
https://www.linkedin.com/feed/update/urn:li:activity:7143579912082288640/
I currently serve the Department of Economics at University of Bergamo as Assistant Professor (RTD-B).
I did my Bachelor and my Master in Statistics and Economics (Dept. of Statistical Sciences P. Fortunati) at University of Bologna, and I obtained there, in 2013, a Phd in Statistical Methodology for the Scientific Research.
In the past, I served University of Salerno (Assistant Professor, Jul 2019 - Jul 2022), University of Brescia (Post-Doc, Lug 2016 - Giu 2019), S.Anna Pisa (Post-Doc, Sep 2015 - Jul 2016) and IMT School for Advanced Studies (Post-Doc, Jun 2013 - Sept 2015).
My research activity focuses on:
• Parametric and semi-parametric spatio-temporal statistical methods for origin-destination data, with application to mobile phone data and mobility
• Sports statistics and data analytics.
• Statistical learning methods for matrix completion
I have published in several international journals (AStA Advances in Statistical Analysis, Physica A, Annals of Operations Research, Social Indicator Research, PlosOne, Econometrics, Natural Hazards and Earth System Sciences, Journal of Applied Statistics, Journal of Quantitative Analysis in Sports, Electronic Journal of Applied Statistical Analysis, Statistics & Applications, The World Economy, Advances in Water Resources, Economia Politica).edit - Massimo Riccaboni (IMT Lucca), Roberto Patuelli (UNIBO), Paola Zuccolotto (UNIBS), Maurizio Carpita (UNIBS), Francesco Giordano (UNISA)edit
Floods are acknowledged as one of the most serious threats to people's lives and properties worldwide. To mitigate the flood risk, it is possible to act separately on its components: hazard, vulnerability, exposure. Emergency management... more
Floods are acknowledged as one of the most serious threats to people's lives and properties worldwide. To mitigate the flood risk, it is possible to act separately on its components: hazard, vulnerability, exposure. Emergency management plans can actually provide effective non-structural practices to decrease both human exposure and vulnerability. Crowding maps depending on characteristic time patterns, herein referred to as dynamic exposure maps, represent a valuable tool to enhance the flood risk management plans. In this paper, the suitability of mobile phone data to derive crowding maps is discussed. A test case is provided by a strongly urbanized area subject to frequent flooding located on the western outskirts of Brescia (northern Italy). Characteristic exposure spatiotemporal patterns and their uncertainties were detected with regard to land cover and calendar period. This novel methodology still deserves verification during real-world flood episodes, even though it appears to be more reliable than crowdsourcing strategies, and seems to have potential to better address real-time rescues and relief supplies.
Research Interests:
Because of the advent of GPS techniques, a wide range of scientific literature on Sport Science is nowadays devoted to the analysis of players' movement in relation to team performance in the context of big data analyt-ics. A specific... more
Because of the advent of GPS techniques, a wide range of scientific literature on Sport Science is nowadays devoted to the analysis of players' movement in relation to team performance in the context of big data analyt-ics. A specific research question regards whether certain patterns of space among players affect team performance, from both an offensive and a defensive perspective. Using a time series of basketball players' coordinates, we focus on the dynamics of the surface area of the five players on the court with a twofold purpose: (i) to give tools allowing a detailed description and analysis of a game with respect to surface areas dynamics and (ii) to investigate its influence on the points made by both the team and the opponent. We propose a three-step procedure integrating different statistical modelling approaches. Specifically , we first employ a Markov Switching Model (MSM) to detect structural changes in the surface area. Then, we perform descriptive analyses in order to highlight associations between regimes and relevant game variables. Finally, we assess the relation between the regime probabilities and the scored points by means of Vector Auto Regressive (VAR) models. We carry out the proposed procedure using real data and, in the analyzed case studies, we find that structural changes are strongly associated to offensive and defensive game phases and that there is some association between the surface area dynamics and the points scored by the team and the opponent.
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This paper investigates the relationship between international trade and migration with the specific aim of estimating direct and indirect effect of the latter on cross-border flows of both homogeneous and differentiated goods. Adopting a... more
This paper investigates the relationship between international trade and migration with the specific aim of estimating direct and indirect effect of the latter on cross-border flows of both homogeneous and differentiated goods. Adopting a spatial econometric approach along with a gravity model set-up, we account for the role of ethnic communities in neighbouring countries on trade, and we propose a new way to define neighbours based on the intensity of links in the migration network. Our approach is particularly well suited to measure the indirect effect stemming from the presence of significant ethnic communities on trade through a “market familiarization” effect. Using data covering all countries between 1970 and 2000, we find a significant indirect effect of migration on trade, that depends on the chosen weight matrix.
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Measuring players' performance in team sports is fundamental since managers need to evaluate players with respect to the ability to score during crucial moments of the game. Using Classification and Regression Trees (CART) and... more
Measuring players' performance in team sports is fundamental since managers need to evaluate players with respect to the ability to score during crucial moments of the game. Using Classification and Regression Trees (CART) and play-by-play basketball data, we estimate the probabilities to score the shot with respect to a selection of game covariates related to game pressure. We use scoring probabilities to develop a player-specific shooting performance index that takes into account for the difficulty associated to score different types of shots. By applying this procedure to a large sample of 2016-2017 Basketball Champions League (BCL) and 2017-2018 National Basketball Association (NBA) games, we compare the factors affecting shooting performance in Europe and in the United States and we evaluate a selection of players in terms of the proposed shooting performance index with the final aim of providing useful guidelines for the team strategy. ARTICLE HISTORY
Research Interests:
Big Data Analytics help team sports' managers in their decisions by processing a number of different kind of data. With the advent of Information Technologies, collecting, processing and storing big amounts of sport data in different form... more
Big Data Analytics help team sports' managers in their decisions by processing a number of different kind of data. With the advent of Information Technologies, collecting, processing and storing big amounts of sport data in different form became possible. A problem that often arises when using sport data regards the need for automatic data cleaning procedures. In this paper we develop a data cleaning procedure for basketball which is based on players' trajectories. Starting from a data matrix that tracks the movements of the players on the court at different moments in the game, we propose an algorithm to automatically drop inactive moments making use of available sensor data. The algorithm also divides the game into sorted actions and labels them as offensive or defensive. The algorithm's parameters are validated using proper robustness checks.
Research Interests:
Nonlinear estimation of the gravity model with Poisson-type regression methods has become popular for modelling international trade flows, because it permits a better accounting for zero flows and extreme values in the distribution tail.... more
Nonlinear estimation of the gravity model with Poisson-type regression methods has become popular for modelling international trade flows, because it permits a better accounting for zero flows and extreme values in the distribution tail. Nevertheless, as trade flows are not independent from each other due to spatial and network autocorrelation, these methods may lead to biased parameter estimates. To overcome this problem, eigenvector spatial filtering (ESF) variants of the Poisson/negative binomial specifications have been proposed in the literature on gravity modelling of trade. However, no specific treatment has been developed for cases in which many zero flows are present. This paper contributes to the literature in two ways. First, by employing a stepwise selection criterion for spatial filters that is based on robust (sandwich) p-values and does not require likelihood-based indicators. In this respect, we develop an ad hoc backward stepwise function in R. Second, using this function, we select a reduced set of spatial filters that properly accounts for importer-side and exporter-side specific spatial effects, as well as network effects, both at the count and the logit processes of zero-inflated methods. Applying this estimation strategy to a cross-section of bilateral trade flows between a set of 64 countries for the year 2000, we find that our specification outperforms the benchmark models in terms of model fitting, both considering the AIC and in predicting zero (and small) flows
Research Interests:
A new approach to performance analysis in team sports consists in studying movements and trajectories of players during the game. State of the art tracking systems produce spatio-temporal traces of players that have facilitated a variety... more
A new approach to performance analysis in team sports consists in studying movements and trajectories of players during the game. State of the art tracking systems produce spatio-temporal traces of players that have facilitated a variety of research aimed to to extract insight from trajectories. Several methods borrowed from machine learning, network and complex systems , geographic information system, computer vision and statistics have been proposed. However, the use of an effective and easy-to-use visual tool in support to these methods is of major importance. To this scope this paper suggests the use of motion charts, built by means of the open-source gvisMotionChart function in googleVis package in R, a user-friendly procedure that also allows to easily import data. A basketball case study is presented. Data refers to a match played by an italian team militant in C-gold league on March 22nd, 2016. Analyses show that motion charts give insights on different spacing structures among offensive and defensive actions, corroborating evidences from other supporting analyses.
Research Interests:
Research Interests:
Disentangling the relations between human migrations and water resources is relevant for food security and trade policy in water-scarce countries. It is commonly believed that human migrations are beneficial to the water endowments of... more
Disentangling the relations between human migrations and water resources is relevant for food security and trade policy in water-scarce countries. It is commonly believed that human migrations are beneficial to the water endowments of origin countries for reducing the pressure on local resources. We show here that such belief is over-simplistic. We reframe the problem by considering the international food trade and the corresponding virtual water fluxes, which quantify the water used for the production of traded agricultural commodities. By means of robust analytical tools, we show that migrants strengthen the commercial links between countries, triggering trade fluxes caused by food consumption habits persisting after migration. Thus migrants significantly increase the virtual water fluxes and the use of water in the countries of origin. The flux ascribable to each migrant, i.e. the " water suitcase " , is found to have increased from 321 m 3 /y in 1990 to 1367 m 3 /y in 2010. A comparison with the water footprint of individuals shows that where the water suitcase exceeds the water footprint of inhabitants, migrations turn out to be detrimental to the water endowments of origin countries, challenging the common perception that migrations tend to relieve the pressure on the local (water) resources of origin countries.
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In this paper we develop a methodology to analyze and compare multiple global networks, focusing our analysis on the relation between human migration and trade. First, we identify the subset of products for which the presence of a... more
In this paper we develop a methodology to analyze and compare multiple global networks, focusing our analysis on the relation between human migration and trade. First, we identify the subset of products for which the presence of a community of migrants significantly increases trade intensity, where to assure comparability across networks we apply a hypergeometric filter that lets us identify those links which intensity is significantly higher than expected. Next, proposing a new way to define country neighbors based on the most intense links in the trade network, we use spatial econometrics techniques to measure the effect of migration on international trade, while controlling for network interdependences. Overall, we find that migration significantly boosts trade across countries and we are able to identify product categories for which this effect is particularly strong.
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Spatial tracking data are used in sport analytics to study the players' position during the game in order to evaluate game strategies, players' roles, performance, also in prospect. From the broad fields of statistics, mathematics,... more
Spatial tracking data are used in sport analytics to study the players' position during the game in order to evaluate game strategies, players' roles, performance, also in prospect. From the broad fields of statistics, mathematics, information science and computer science it is possible to draw theories and methods useful to produce innovative results based on speed, distance, players' separation trajectories. In basketball , spatial tracking data can be combined with play-by-play data, joining results on spatial movements to team performance. In this paper, using tracking data from basketball, we study the spatial pattern of players on the court in order to contribute to the literature of data mining methods for tracking data analysis in sports, with the final objective of suggesting new game strategies to improve team performance.
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The relationship between international trade and foreign direct investment (FDI) is one of the main features of globalization. In this paper we investigate the effects of FDI on trade from a network perspective, since FDI takes not only... more
The relationship between international trade and foreign direct investment (FDI) is one of the main features of globalization. In this paper we investigate the effects of FDI on trade from a network perspective, since FDI takes not only direct but also indirect channels from origin to destination countries because of firms’ incentive to reduce tax burden, to minimize coordination costs, and to break barriers to market entry. We use a unique data set of international corporate control as a measure of stock FDI to construct a corporate control network (CCN) where the nodes are the countries and the edges are the corporate control relationships.
Based on the CCN, the network measures, i.e., the shortest path
length and the communicability, are computed to capture the indirect
channel of FDI. Empirically we find that corporate control has a positive
effect on trade both directly and indirectly. The result is robust with different specifications and estimation strategies. Hence, our paper provides strong empirical evidence of the indirect effects of FDI on trade. Moreover, we identify a number of interplaying factors such as regional trade agreements and the region of Asia. We also find that the indirect effects are more pronounced for manufacturing sectors than for primary sectors such as oil extraction and agriculture
Based on the CCN, the network measures, i.e., the shortest path
length and the communicability, are computed to capture the indirect
channel of FDI. Empirically we find that corporate control has a positive
effect on trade both directly and indirectly. The result is robust with different specifications and estimation strategies. Hence, our paper provides strong empirical evidence of the indirect effects of FDI on trade. Moreover, we identify a number of interplaying factors such as regional trade agreements and the region of Asia. We also find that the indirect effects are more pronounced for manufacturing sectors than for primary sectors such as oil extraction and agriculture
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In light of growing water scarcity, virtual water, or the water embedded in key water-intensive commodities, has been an active area of debate among practitioners and academics alike. As of yet, however, there is no consensus on whether... more
In light of growing water scarcity, virtual water, or the water embedded in key water-intensive commodities, has been an active area of debate among practitioners and academics alike. As of yet, however, there is no consensus on whether water scarcity affects conflict behavior and we still lack empirical research intending to account for the role of virtual water in affecting the odds of militarized disputes between states. Using quantitative methods and data on virtual water trade, we find that bilateral and multilateral trade openness reduce the probability of war between any given pair of country, which is consistent with the strategic role of this important commodity and the opportunity cost associated with the loss of trade gains. We also find that the substantive effect of
virtual water trade is comparable to that of oil and gas, the archetypal natural resources, in determining interstate conflicts’ probability
virtual water trade is comparable to that of oil and gas, the archetypal natural resources, in determining interstate conflicts’ probability
Research Interests:
To analyze the movements and to study the trajectories of players is a crucial need for a team when he looks to improve its chances of winning a match or to understand its performances. State of the art tracking systems now produce... more
To analyze the movements and to study the trajectories of players is a crucial need for a team when he looks to improve its chances of winning a match or to understand its performances. State of the art tracking systems now produce spatio-temporal traces of player trajectories with high definition and frequency that has facilitated a variety of research efforts to extract insight from the trajectories. Despite many methods borrowed from different disciplines (machine learning, network and complex systems, GIS, computer vision, statistics) has been proposed to answer to the needs of teams, a friendly and easy-to-use approach to visualize spatio-temporal movements is still missing. This paper suggests the use of gvisMotionChart function in googleVis R package. I present and discuss results of a basketball case study. Data refers to a match played by an italian team militant in " C-gold " league on March 22nd, 2016. With this case study I show that such a visualization approach could be useful in supporting researcher on preliminar stages of their analysis on sports' movements, and to facilitate the interpretation of their results.
Research Interests:
Nonlinear estimation of the gravity model with Poisson/negative binomial methods has become popular to model international trade flows, because it permits a better accounting for zero flows and extreme values in the distribution tail.... more
Nonlinear estimation of the gravity model with Poisson/negative binomial methods has become popular to model international trade flows, because it permits a better accounting for zero flows and extreme values in the distribution tail. Nevertheless, as trade flows are not independent from each other due to spatial autocorrelation, these methods may lead to biased parameter estimates. To overcome this problem, eigenvector spatial filtering variants of the Poisson/negative binomial specification have been proposed in the literature of gravity
modelling of trade. However, no specific treatment has been developed for cases in which many zero flows are present. This paper contributes to the literature in two ways. First, by employing a stepwise selection criterion for spatial filters that is based on robust (sandwich) p-values and does not require likelihood-based indicators. In this respect, we develop an ad hoc backward stepwise function in R. Second, using this function, we select a reduced set of spatial filters that properly accounts for importer-side and exporter-side specific spatial effects, both at the count and the logit processes of zero-inflated methods. Applying this
estimation strategy to a cross-section of bilateral trade flows between a set of worldwide countries for the year 2000, we find that our specification outperforms the benchmark models in terms of model fitting, both considering the AIC and in predicting zero (and small) flows.
modelling of trade. However, no specific treatment has been developed for cases in which many zero flows are present. This paper contributes to the literature in two ways. First, by employing a stepwise selection criterion for spatial filters that is based on robust (sandwich) p-values and does not require likelihood-based indicators. In this respect, we develop an ad hoc backward stepwise function in R. Second, using this function, we select a reduced set of spatial filters that properly accounts for importer-side and exporter-side specific spatial effects, both at the count and the logit processes of zero-inflated methods. Applying this
estimation strategy to a cross-section of bilateral trade flows between a set of worldwide countries for the year 2000, we find that our specification outperforms the benchmark models in terms of model fitting, both considering the AIC and in predicting zero (and small) flows.
Research Interests:
Research Interests:
The Gravity Model is the workhorse for empirical studies in International Economies and it is commonly used in explaining the trade flow between countries. Recently, several studies have showed the importance of taking into account the... more
The Gravity Model is the workhorse for empirical studies in International
Economies and it is commonly used in explaining the trade flow
between countries. Recently, several studies have showed the importance
of taking into account the spatial effect. Spatial Econometric
techniques meet this matter, proposing the specification of a set of
models and estimators. We will make use of these Spatial Econometric
techniques in order to estimate a Spatial Gravity of Trade for
a 22-year-long panel of the OECD countries. The aim, therefore, is
twofold: on one hand, we are going to use the newest Spatial Econometric
techniques in a field where they aren't widely applicated. On
the other hand, we provide an updated interpretation of the behaviour
of the International Trade in an OECD context, taking into account
potential spatial spillover effect due to the third country dependence,
and the effects of the migratory phenomenon.
Economies and it is commonly used in explaining the trade flow
between countries. Recently, several studies have showed the importance
of taking into account the spatial effect. Spatial Econometric
techniques meet this matter, proposing the specification of a set of
models and estimators. We will make use of these Spatial Econometric
techniques in order to estimate a Spatial Gravity of Trade for
a 22-year-long panel of the OECD countries. The aim, therefore, is
twofold: on one hand, we are going to use the newest Spatial Econometric
techniques in a field where they aren't widely applicated. On
the other hand, we provide an updated interpretation of the behaviour
of the International Trade in an OECD context, taking into account
potential spatial spillover effect due to the third country dependence,
and the effects of the migratory phenomenon.
Research Interests:
This paper studies the relationship between migration and trade, with the aim of measuring both direct and indirect network effects. We analyze trade of diferentiated and homogeneous goods using an econometric approach inspired by spatial... more
This paper studies the relationship between migration and trade, with the aim of measuring both direct and indirect network effects. We analyze trade of diferentiated and homogeneous goods using an econometric approach inspired by spatial econometrics, proposing a new way to define country neighbors based on the most intense links in the migration network. We find that migration significantly affects trade across categories both in direct and in indirect way. The indirect impact highlights a stronger competitive effect of third country migrants for homogeneous goods. We also confirm that the effect of migration channels is higher on differentiated goods.
Research Interests:
Water scarcity reduction is one of the main challenge in the new millennium. The concepts of Virtual Water (VW) footprint and VW trade are foundant in respect to analyze water scarcity issues. Jose Graziano Da Silva at the last... more
Water scarcity reduction is one of the main challenge in the new millennium. The concepts of Virtual Water (VW) footprint and VW trade are foundant in respect to analyze water scarcity issues. Jose Graziano Da Silva at the last ministerial FAO meeting armed that the worsening of food security depends, by others, on migration phenomena. Arab Spring, burst in December 2010,
increased the number of migrants (in particular from the Near East). With this paper we analyze, by mean of the gravity equation, the relation between VW trade and migration from an Econometric
point of view. We propose and determine a measure of VW impact for each migrant, which we call Vitual Water Suitcase. We use this measure to conclude with some policy recommendation.
increased the number of migrants (in particular from the Near East). With this paper we analyze, by mean of the gravity equation, the relation between VW trade and migration from an Econometric
point of view. We propose and determine a measure of VW impact for each migrant, which we call Vitual Water Suitcase. We use this measure to conclude with some policy recommendation.
Research Interests:
The Gravity Model is the workhorse for empirical studies in International Economies and it is commonly used in explaining the trade flow between countries. Recently, several studies have showed the importance of taking into account the... more
The Gravity Model is the workhorse for empirical studies in International Economies and it is commonly used in explaining the trade flow between countries.
Recently, several studies have showed the importance of taking into account the spatial effect. The standard procedure until now was to account the transport cost using geographical distance as a proxy, and the spatial effect trough a weighted matrix constructed on inverse distance. Two issues follow from this standard procedure: the first regards the biasness of the distance if used as a proxy of the transport costs, the second is related to the collinearity emerging if we use distance twice. So, several attempt were made in the recent literature having the scope of remove the distance. We propose a theoretically consistent procedure based on Anderson, Van Wincoop derivation model, and some ad-hoc tests, relating to this attempt. The empirical results based on a 22-years panel of OECD countries are conforting, and they allow us to estimate the model without the distance, if properly replaced by a set of fixed effects.
Recently, several studies have showed the importance of taking into account the spatial effect. The standard procedure until now was to account the transport cost using geographical distance as a proxy, and the spatial effect trough a weighted matrix constructed on inverse distance. Two issues follow from this standard procedure: the first regards the biasness of the distance if used as a proxy of the transport costs, the second is related to the collinearity emerging if we use distance twice. So, several attempt were made in the recent literature having the scope of remove the distance. We propose a theoretically consistent procedure based on Anderson, Van Wincoop derivation model, and some ad-hoc tests, relating to this attempt. The empirical results based on a 22-years panel of OECD countries are conforting, and they allow us to estimate the model without the distance, if properly replaced by a set of fixed effects.
Research Interests:
Research Interests:
IMT Institute for Advanced Studies, nelle persone di Massimo Riccaboni, Rodolfo Metulini, Francesco Biancalani e Roberto Catini, ha svolto questo rapporto sullo stato economico e demografico del territorio lucchese, richiesto dalla... more
IMT Institute for Advanced Studies, nelle persone di Massimo Riccaboni, Rodolfo Metulini, Francesco Biancalani e Roberto Catini, ha svolto questo rapporto sullo stato economico e demografico del territorio lucchese, richiesto dalla commissione urbanistica del comune di Lucca all’interno del piano strutturale 2014. Il report, verte a valutare le conseguenze della crisi sul territorio lucchese, descrivendo la situazione attuale ed il trend economico del recente passato, cercando di inserirla in un contesto più ampio in cui la dimensione economica entra in relazione con la struttura socio-demografica, tessuto manifatturiero e l'andamento dell'edilizia.
Il rapporto attinge da svariate fonti esterne, tra le quali possiamo citare ISTAT, Banca d’Italia, Camera di Commercio e Agenzia delle Entrate, mentre la parte centrale dei risultati che verranno presentati sono stati estratti dal database Orbis. Il database mette a disposizione indicatori economici di bilancio (quali ricavi operativi e capitali investiti) per 7409 imprese di diverso ordine e dimensione presenti in provincia. Il rapporto si snoda lungo 4 capitoli principali, ognuno dei quali si pone obiettivi specifici ma interconnessi tra loro:
Nel primo capitolo viene presentata la situazione demografica del territorio, in termini di popolazione residente e sua distribuzione per fasce d’età e istruzione, saldo naturale e quota di immigrati.
Il secondo capitolo fa luce sulla situazione economica della città, con un'analisi dettagliata relativa alla quantificazione delle imprese e del loro trend in termini di ricavi operativi, numero di dipendenti, capitali investiti, Return on Equity (ROE) e Return on Assets (ROA).
Il terzo capitolo entra in maggiore dettaglio, presentando i risultati dei principali indicatori economici a livello settoriale e per macro aree geografiche (Piana di Lucca, Versilia, Garfagnana, Media Valle). Vengono poi analizzati i settori che nel periodo studiato (2007-2013) sono stati maggiormente competitivi. Inoltre, vengono presentati altri indicatori sulla qualità della vita, relativi all’occupazione e al livello di imprenditorialità, investimenti in formazione e propensione all’export. Chiude una sezione dedicata al turismo. Si fa anche luce sulla distribuzione geografica delle imprese, allo scopo di capire come la città di Lucca riveste un ruolo centrale nell’economia del territorio, considerando le dotazioni infrastrutturali in relazione all’afflusso turistico.
Il quarto capitolo ha lo scopo di inquadrare la situazione immobiliare lucchese rispetto al contesto regionale e nazionale, relativamente ai prezzi di acquisto e affitto, l’indice di affordability e con particolare riguardo all’analisi dei “contenitori” vuoti, per il quale viene svolta una stima degli immobili inutilizzati
Il rapporto attinge da svariate fonti esterne, tra le quali possiamo citare ISTAT, Banca d’Italia, Camera di Commercio e Agenzia delle Entrate, mentre la parte centrale dei risultati che verranno presentati sono stati estratti dal database Orbis. Il database mette a disposizione indicatori economici di bilancio (quali ricavi operativi e capitali investiti) per 7409 imprese di diverso ordine e dimensione presenti in provincia. Il rapporto si snoda lungo 4 capitoli principali, ognuno dei quali si pone obiettivi specifici ma interconnessi tra loro:
Nel primo capitolo viene presentata la situazione demografica del territorio, in termini di popolazione residente e sua distribuzione per fasce d’età e istruzione, saldo naturale e quota di immigrati.
Il secondo capitolo fa luce sulla situazione economica della città, con un'analisi dettagliata relativa alla quantificazione delle imprese e del loro trend in termini di ricavi operativi, numero di dipendenti, capitali investiti, Return on Equity (ROE) e Return on Assets (ROA).
Il terzo capitolo entra in maggiore dettaglio, presentando i risultati dei principali indicatori economici a livello settoriale e per macro aree geografiche (Piana di Lucca, Versilia, Garfagnana, Media Valle). Vengono poi analizzati i settori che nel periodo studiato (2007-2013) sono stati maggiormente competitivi. Inoltre, vengono presentati altri indicatori sulla qualità della vita, relativi all’occupazione e al livello di imprenditorialità, investimenti in formazione e propensione all’export. Chiude una sezione dedicata al turismo. Si fa anche luce sulla distribuzione geografica delle imprese, allo scopo di capire come la città di Lucca riveste un ruolo centrale nell’economia del territorio, considerando le dotazioni infrastrutturali in relazione all’afflusso turistico.
Il quarto capitolo ha lo scopo di inquadrare la situazione immobiliare lucchese rispetto al contesto regionale e nazionale, relativamente ai prezzi di acquisto e affitto, l’indice di affordability e con particolare riguardo all’analisi dei “contenitori” vuoti, per il quale viene svolta una stima degli immobili inutilizzati
Research Interests:
Questo Documento riporta un insieme di analisi volte a misurare la copertura dei costi relativi all’acqua, sostenuti dai gestori dei servizi idrici entro il perimetro dell’area di Bacino del fiume Serchio. Tale lavoro deve essere svolto... more
Questo Documento riporta un insieme di analisi volte a misurare la copertura dei costi relativi all’acqua, sostenuti dai gestori dei servizi idrici entro il perimetro dell’area di Bacino del fiume Serchio. Tale lavoro deve essere svolto per legge a seguito della direttiva 2000/60/CE della Comunità Europea, per il Bacino del Serchio, cosi come per tutti i bacini fluviali presenti in Italia ed in Europa. Nel dettaglio, nel Capitolo 1 vengono definiti i costi cosi come vengono strutturati dalla direttiva (costi finanziari, della risorsa, ambientali), e i metodi di stima (n.d.r metodi tariffari) definiti allo scopo di una corretta misurazione dei costi. il Capitolo 2 presenta una caratterizzazione del tessuto socio-economica e demografica all’interno dell’rea di Bacino. Il Capitolo 3 copre l’argomento della copertura dei costi in ambito civile, con una dettagliata presentazione dei gestori locali. Il Capitolo 4 sposta l’attenzione sulla copertura dei costi in ambito agricolo, e propone inoltre un metodo innovativo per la misurazione del costo della risorsa idrica basato sulla comparazione del margine lordo d’impresa sulla base della percentuale di superficie irrigata. Il Capitolo 5 conclude il documento introducendo l’aspetto del costo della risorsa idrica in ambito industriale.
Research Interests:
Because of the advent of GPS techniques, a wide range of scientific literature on Sport Science is nowadays devoted to the analysis of players’ movement in relation to team performance in the context of big data analytics. A specific... more
Because of the advent of GPS techniques, a wide range of scientific literature on Sport Science is nowadays devoted to the analysis of players’ movement in relation to team performance in the context of big data analytics. A specific research question regards whether certain patterns of space among players affect team performance, from both an offensive and a defensive perspective. Using a time series of basketball players’ coordinates, we focus on the dynamics of the surface area of the five players on the court with a two-fold purpose: (i) to give tools allowing a detailed description and analysis of a game with respect to surface areas dynamics and (ii) to investigate its influence on the points made by both the team and the opponent. We propose a three-step procedure integrating different statistical modelling approaches. Specifically, we first employ a Markov Switching Model (MSM) to detect structural changes in the surface area. Then, we perform descriptive analyses in order to highlight associations between regimes and relevant game variables. Finally, we assess the relation between the regime probabilities and the scored points by means of Vector Auto Regressive (VAR) models. We carry out the proposed procedure using real data and, in the analyzed case studies, we find that structural changes are strongly associated to offensive and defensive game phases and that there is some association between the surface area dynamics and the points scored by the team and the opponent.
Research Interests:
Global Positioning System (GPS) devices capture the location on space of entities repeatedly over time, generating spatio-temporal data. These devices are nowadays intensively used in team sports to capture the trajectories of players and... more
Global Positioning System (GPS) devices capture the location on space of entities
repeatedly over time, generating spatio-temporal data. These devices are nowadays intensively used
in team sports to capture the trajectories of players and /or the ball -sometimes together with playby-
play recording the time of match events - with the aim of infer useful informations to coaches in
addition to traditional statistics.
In our application to basketball, we collected sensor data related to the location of players during
all the official matches played by a team militant in the “C-Gold” league in Italy. Data reports x-axis
(width), y-axis (length) and z-axis (height) coordinates for a time series recorded at millisecond level.
The play-by-play reports relevant events (such as made shots, fouls, etc ...) together with their moment
in time.
The aim of this study is to find any regularities and synchronization in basketball players movements,
with the final objective of extracting insights on the relations between particular spatial patterns
and the performance of the team. By means of different statistical techniques, such as Cluster Analysis,
MultiDimensional Scaling (MDS) and Principal Components Analysis (PCA) we split the match
in a number of groups, each identifying homogeneous spatial relations among players in the field.
These methods permit to characterize groups in terms of some relevant properties, such as differences
in spacings among players, whether each group corresponds to defensive or offensive actions,
or in terms of the transition probability from a certain group to another one. Results of this kind of
analysis are the starting point for identifying a possible relationship between the identified patterns -in
terms of players’ spatial relations- and the team’s performance -in terms of field goals percentage or
other relevant match events.
repeatedly over time, generating spatio-temporal data. These devices are nowadays intensively used
in team sports to capture the trajectories of players and /or the ball -sometimes together with playby-
play recording the time of match events - with the aim of infer useful informations to coaches in
addition to traditional statistics.
In our application to basketball, we collected sensor data related to the location of players during
all the official matches played by a team militant in the “C-Gold” league in Italy. Data reports x-axis
(width), y-axis (length) and z-axis (height) coordinates for a time series recorded at millisecond level.
The play-by-play reports relevant events (such as made shots, fouls, etc ...) together with their moment
in time.
The aim of this study is to find any regularities and synchronization in basketball players movements,
with the final objective of extracting insights on the relations between particular spatial patterns
and the performance of the team. By means of different statistical techniques, such as Cluster Analysis,
MultiDimensional Scaling (MDS) and Principal Components Analysis (PCA) we split the match
in a number of groups, each identifying homogeneous spatial relations among players in the field.
These methods permit to characterize groups in terms of some relevant properties, such as differences
in spacings among players, whether each group corresponds to defensive or offensive actions,
or in terms of the transition probability from a certain group to another one. Results of this kind of
analysis are the starting point for identifying a possible relationship between the identified patterns -in
terms of players’ spatial relations- and the team’s performance -in terms of field goals percentage or
other relevant match events.
Research Interests:
Research Interests:
In this document some Kriskograms are used as a tool to visually analyze the evolution over time of the worldwide Virtual Water network (yearly flows).
Plots are reported for the years 1990, 1995, 2000, 2005 and 2010.
Plots are reported for the years 1990, 1995, 2000, 2005 and 2010.
Research Interests:
Research Interests:
This paper study the relation between International Trade and Foreign Direct Investment (FDI) in the world economy. First we study the prob- lem in a multiple-network perspective, showing that the two networks are strongly correlated... more
This paper study the relation between International Trade and Foreign
Direct Investment (FDI) in the world economy. First we study the prob-
lem in a multiple-network perspective, showing that the two networks
are strongly correlated and that such correlation can be mostly explained by country economic/demographic size and geographical distance. Then, using the Heckman selection model with a gravity equation, we con rm this result and also nd that the industry position in the Global Supply Chain (GSC) and countries distance give rise to non-linear corrections: in particular we nd that the more goods are downstream or countries are further away, the more trade and FDI tend to be complements. Next we investigate the e ects of Regional Trade Agreements and the special case of Asian countries. Finally we distinguish the cases of the three main economic macro-sectors, nding that trade and FDI are complements in manufacturing, but substitutes in services.
Direct Investment (FDI) in the world economy. First we study the prob-
lem in a multiple-network perspective, showing that the two networks
are strongly correlated and that such correlation can be mostly explained by country economic/demographic size and geographical distance. Then, using the Heckman selection model with a gravity equation, we con rm this result and also nd that the industry position in the Global Supply Chain (GSC) and countries distance give rise to non-linear corrections: in particular we nd that the more goods are downstream or countries are further away, the more trade and FDI tend to be complements. Next we investigate the e ects of Regional Trade Agreements and the special case of Asian countries. Finally we distinguish the cases of the three main economic macro-sectors, nding that trade and FDI are complements in manufacturing, but substitutes in services.
Research Interests:
This paper studies the relationship between migration and trade, with the aim of measuring both direct and indirect network effects. We analyze trade of diferentiated and homogeneous goods using an econometric approach inspired by... more
This paper studies the relationship between migration and trade, with the aim of measuring
both direct and indirect network effects. We analyze trade of diferentiated and homogeneous
goods using an econometric approach inspired by spatial econometrics, proposing a new
way to define country neighbors based on the most intense links in the migration network.
We find that migration significantly affects trade across categories both in direct and in
indirect way. The indirect impact highlights a stronger competitive effect of third country
both direct and indirect network effects. We analyze trade of diferentiated and homogeneous
goods using an econometric approach inspired by spatial econometrics, proposing a new
way to define country neighbors based on the most intense links in the migration network.
We find that migration significantly affects trade across categories both in direct and in
indirect way. The indirect impact highlights a stronger competitive effect of third country
Research Interests:
Research Interests:
This 10 hours class is intended to give students the basis to empirically solve statistical problems. Talk 1 serves as an introduction to the statistical software R, and presents how to calculate basic measures such as mean, variance,... more
This 10 hours class is intended to give students the basis to empirically solve statistical problems. Talk 1 serves as an introduction to the statistical software R, and presents how to calculate basic measures such as mean, variance, correlation and gini index. Talk 2 shows how the central limit theorem and the law of the large numbers work empirically. Talk 3 presents the point estimate, the confidence interval and the hypothesis test for the most important parameters. Talk 4 introduces to the linear regression model and Talk 5 to the bootstrap world. Talk 5 also presents an easy example of a markov chains.
All the talks are supported by script codes, in R language.
All the talks are supported by script codes, in R language.
Research Interests:
Research Interests:
Research Interests:
Queste slides sono state preparate per presentare il documento dell'analisi economica del piano di Bacino. Tale analisi è volta a misurare la copertura dei costi relativi all’acqua, sostenuti dai gestori dei servizi idrici entro il... more
Queste slides sono state preparate per presentare il documento dell'analisi economica del piano di Bacino.
Tale analisi è volta a misurare la copertura dei costi relativi all’acqua, sostenuti dai gestori dei servizi idrici entro il perimetro dell’area di Bacino del fiume Serchio. Tale lavoro deve essere svolto per legge a seguito della direttiva 2000/60/CE della Comunità Europea, per il Bacino del Serchio, cosi come per tutti i bacini fluviali presenti in Italia ed in Europa. Nel dettaglio, nel Capitolo 1 vengono definiti i costi cosi come vengono strutturati dalla direttiva (costi finanziari, della risorsa, ambientali), e i metodi di stima (n.d.r metodi tariffari) definiti allo scopo di una corretta misurazione dei costi. il Capitolo 2 presenta una caratterizzazione del tessuto socio-economica e demografica all’interno dell’rea di Bacino. Il Capitolo 3 copre l’argomento della copertura dei costi in ambito civile, con una dettagliata presentazione dei gestori locali. Il Capitolo 4 sposta l’attenzione sulla copertura dei costi in ambito agricolo, e propone inoltre un metodo innovativo per la misurazione del costo della risorsa idrica basato sulla comparazione del margine lordo d’impresa sulla base della percentuale di superficie irrigata. Il Capitolo 5 conclude il documento introducendo l’aspetto del costo della risorsa idrica in ambito industriale.
Tale analisi è volta a misurare la copertura dei costi relativi all’acqua, sostenuti dai gestori dei servizi idrici entro il perimetro dell’area di Bacino del fiume Serchio. Tale lavoro deve essere svolto per legge a seguito della direttiva 2000/60/CE della Comunità Europea, per il Bacino del Serchio, cosi come per tutti i bacini fluviali presenti in Italia ed in Europa. Nel dettaglio, nel Capitolo 1 vengono definiti i costi cosi come vengono strutturati dalla direttiva (costi finanziari, della risorsa, ambientali), e i metodi di stima (n.d.r metodi tariffari) definiti allo scopo di una corretta misurazione dei costi. il Capitolo 2 presenta una caratterizzazione del tessuto socio-economica e demografica all’interno dell’rea di Bacino. Il Capitolo 3 copre l’argomento della copertura dei costi in ambito civile, con una dettagliata presentazione dei gestori locali. Il Capitolo 4 sposta l’attenzione sulla copertura dei costi in ambito agricolo, e propone inoltre un metodo innovativo per la misurazione del costo della risorsa idrica basato sulla comparazione del margine lordo d’impresa sulla base della percentuale di superficie irrigata. Il Capitolo 5 conclude il documento introducendo l’aspetto del costo della risorsa idrica in ambito industriale.
Research Interests:
Research Interests:
In the context of Smart Cities, local institutions face the increasing need for monitoring the dynamic of the flow of people’s presences inside urban areas in order to plan the improvement and the maintaining of the urban infrastructure.... more
In the context of Smart Cities, local institutions face the increasing need for monitoring the dynamic of the flow of people’s presences inside urban areas in order to plan the improvement and the maintaining of the urban infrastructure. Rectangular grid polygons reporting the density
of people using mobile phone (Carpita, Simonetto, 2014) are source of very large data. Telecom Italia Mobile (TIM), which is currently the largest operator in Italy in this sector, thanks to a research agreement with the Statistical Office of the Municipality of Brescia, provided to us
about two years (April 2014 to June 2016, n ' 700) of Daily Mobile Phone Density Profiles (DMPDPs) for the Province of Brescia in the form of a regular grid of 923 x 607 cells each 15 minutes.
In order to find regularities and detect anomalies in the flow of people’s presences, this work aims to cluster similar DMPDPs, where each DMPDP is characterized by both the 2-D spatial component (i.e. 923 x 607 dimensions, one for each cell of the grid) and by the temporal
component (i.e. each cell has repeated values in time, for a total of 96 daily dimensions per cell). So, while each DMPDP counts for p ' 50 millions (923 x 607 x 96) of space-time dimensions, time and economic constraints prevent us from having a longer time series of DMPDPs. In
this terms, to group DMPDPs configures as an High Dimensional Low Sample Size (HDLSS) problem, since p is smaller than n.
We propose a mixed-approach procedure that we apply to the city of Brescia. First, borrowing the method of the Histogram of Oriented Gradients (HOG) from the Image Clustering discipline (Tomasi, 2012), we perform a reduction of the DMPDPs dimensionality computing
their features extractions. In doing so, we perform some tuning on the HOG parameters in order to reduce as much as possible the DMPDPs dimensionality while preserving as much as possible the information contained in the extracted features. With this approach we preserve both the spatial and the temporal components of the DMPDPs. Then, using the HOG features extractions, we group DMPDPs by applying - and by testing the feasibility of - different clustering
approaches for large data. We finally represent each cluster's DMPDP in terms of tensor decomposition.
of people using mobile phone (Carpita, Simonetto, 2014) are source of very large data. Telecom Italia Mobile (TIM), which is currently the largest operator in Italy in this sector, thanks to a research agreement with the Statistical Office of the Municipality of Brescia, provided to us
about two years (April 2014 to June 2016, n ' 700) of Daily Mobile Phone Density Profiles (DMPDPs) for the Province of Brescia in the form of a regular grid of 923 x 607 cells each 15 minutes.
In order to find regularities and detect anomalies in the flow of people’s presences, this work aims to cluster similar DMPDPs, where each DMPDP is characterized by both the 2-D spatial component (i.e. 923 x 607 dimensions, one for each cell of the grid) and by the temporal
component (i.e. each cell has repeated values in time, for a total of 96 daily dimensions per cell). So, while each DMPDP counts for p ' 50 millions (923 x 607 x 96) of space-time dimensions, time and economic constraints prevent us from having a longer time series of DMPDPs. In
this terms, to group DMPDPs configures as an High Dimensional Low Sample Size (HDLSS) problem, since p is smaller than n.
We propose a mixed-approach procedure that we apply to the city of Brescia. First, borrowing the method of the Histogram of Oriented Gradients (HOG) from the Image Clustering discipline (Tomasi, 2012), we perform a reduction of the DMPDPs dimensionality computing
their features extractions. In doing so, we perform some tuning on the HOG parameters in order to reduce as much as possible the DMPDPs dimensionality while preserving as much as possible the information contained in the extracted features. With this approach we preserve both the spatial and the temporal components of the DMPDPs. Then, using the HOG features extractions, we group DMPDPs by applying - and by testing the feasibility of - different clustering
approaches for large data. We finally represent each cluster's DMPDP in terms of tensor decomposition.
Research Interests:
Global Positioning Systems (GPS) are nowadays intensively used in Sport Science as they capture the trajectories of players and /or the ball, sometimes together with play-by-play recording the time of match events, with the aim to supply... more
Global Positioning Systems (GPS) are nowadays intensively used in Sport Science as they capture the trajectories
of players and /or the ball, sometimes together with play-by-play recording the time of match events, with the aim
to supply coaches, experts and analysts with useful information in addition to traditional statistics. To find any
regularities and synchronizations in players‘ trajectories, and to study their relationship with team's performance,
however, is a complex task, because of the strong interdependencies among players in the court and because of external
factors that can influence players. To this aim, a variety of methods has been proposed in Sport Science literature,
which borrow from the disciplines of Machine Learning, Network and Complex Systems, Geographical Information Systems,
Computer Vision and Statistics. In this seminar, with an application to basketball, I propose a methodological approach that
can be generalized to other team sports. I first demonstrate the usefulness of a visual tool approach in order to extract
preliminar insights from trajectories, then, I use data mining techniques such as Cluster Analysis and Multidimensional
Scaling to decompose the game into homogeneous phases in terms of spatial relations. To conclude, I present specific
research questions, such as: i) who is the most influencing player of the team? ii) how much each player influences the others?
iii) how much trajectories are determined by trajectories of other players and by external factors? where the adoption of
methods traditionally used in Spatial Statistics and Spatial Econometrics could have a potential. In this regard, the seminar
is also intended as a “platform” to launch new research challenges and to search for collaboration.
Acknowledgements: The research is carried out thanks to sensor data made available by MyAgonism.
of players and /or the ball, sometimes together with play-by-play recording the time of match events, with the aim
to supply coaches, experts and analysts with useful information in addition to traditional statistics. To find any
regularities and synchronizations in players‘ trajectories, and to study their relationship with team's performance,
however, is a complex task, because of the strong interdependencies among players in the court and because of external
factors that can influence players. To this aim, a variety of methods has been proposed in Sport Science literature,
which borrow from the disciplines of Machine Learning, Network and Complex Systems, Geographical Information Systems,
Computer Vision and Statistics. In this seminar, with an application to basketball, I propose a methodological approach that
can be generalized to other team sports. I first demonstrate the usefulness of a visual tool approach in order to extract
preliminar insights from trajectories, then, I use data mining techniques such as Cluster Analysis and Multidimensional
Scaling to decompose the game into homogeneous phases in terms of spatial relations. To conclude, I present specific
research questions, such as: i) who is the most influencing player of the team? ii) how much each player influences the others?
iii) how much trajectories are determined by trajectories of other players and by external factors? where the adoption of
methods traditionally used in Spatial Statistics and Spatial Econometrics could have a potential. In this regard, the seminar
is also intended as a “platform” to launch new research challenges and to search for collaboration.
Acknowledgements: The research is carried out thanks to sensor data made available by MyAgonism.
Research Interests:
This tutorial show how to visualize spatio-temporal movements of basketball players within the court using gvisMotionChart function in googleVis, R Package. Enjoy! http://www.mathpubs.com/detail/1611.0...... more
This tutorial show how to visualize spatio-temporal movements of basketball players within the court using gvisMotionChart function in googleVis, R Package.
Enjoy!
http://www.mathpubs.com/detail/1611.0...
http://bodai.unibs.it/BDSports/
http://bodai.unibs.it/public/index.php
Enjoy!
http://www.mathpubs.com/detail/1611.0...
http://bodai.unibs.it/BDSports/
http://bodai.unibs.it/public/index.php
Research Interests:
Research Interests:
Disentangling the relations between human migrations and water resources is relevant for food security and trade policy in water-scarce countries. It is commonly believed that human migrations are beneficial to the water endowments of... more
Disentangling the relations between human migrations and water resources is relevant for food security and trade policy in water-scarce countries. It is commonly believed that human migrations are beneficial to the water endowments of origin countries for reducing the pressure on local resources. We show here that such belief is over-simplistic. We reframe the problem by considering the international food trade and the corresponding virtual water fluxes, which quantify the water used for the production of traded agricultural commodities. By means of robust analytical tools, we show that migrants strengthen the commercial links between countries, triggering trade fluxes caused by food consumption habits persisting after migration. Thus migrants significantly increase the virtual water fluxes and the use of water in the countries of origin. The flux ascribable to each migrant, i.e. the “water suitcase”, is found to have increased from 321 m3/y in 1990 to 1367 m3/y in 2010. A comparison with the water footprint of individuals shows that where the water suitcase exceeds the water footprint of inhabitants, migrations turn out to be detrimental to the water endowments of origin countries, challenging the common perception that migrations tend to relieve the pressure on the local (water) resources of origin countries.
Research Interests:
Due to the advent of GPS techniques, a wide range of scientific literature on Sport Science is nowadays devoted to the analysis of players movement in relation to team performance in the context of big data analytics. A specific research... more
Due to the advent of GPS techniques, a wide range of scientific literature on Sport Science is nowadays devoted to the analysis of players movement
in relation to team performance in the context of big data analytics. A specific research question regards whether certain patterns of space among
players affect team performance, from both an offensive and a defensive perspective. Using a time series of basketball players coordinates, we
focus on the dynamics of the surface area of the five players on the court with a twofold purpose: (i) to give tools allowing a detailed description and
analysis of a game with respect to surface areas dynamics and (ii) to investigate its influence on the points made by both the team and the opponent.
We propose a three-step procedure integrating different statistical modelling approaches. Specifically, we first employ a Markov Switching Model
(MSM) to detect structural changes in the surface area. Then, we perform descriptive analyses in order to highlight associations between regimes
and relevant game variables. Finally, we assess the relation between the regime probabilities and the scored points by means of Vector Auto
Regressive (VAR)models. We carry out the proposed procedure using real data and, in the analyzed case studies, we find that structural changes
are strongly associated to offensive and defensive game phases and that there is some association between the surface area dynamics and the points
scored by the team and the opponent.
in relation to team performance in the context of big data analytics. A specific research question regards whether certain patterns of space among
players affect team performance, from both an offensive and a defensive perspective. Using a time series of basketball players coordinates, we
focus on the dynamics of the surface area of the five players on the court with a twofold purpose: (i) to give tools allowing a detailed description and
analysis of a game with respect to surface areas dynamics and (ii) to investigate its influence on the points made by both the team and the opponent.
We propose a three-step procedure integrating different statistical modelling approaches. Specifically, we first employ a Markov Switching Model
(MSM) to detect structural changes in the surface area. Then, we perform descriptive analyses in order to highlight associations between regimes
and relevant game variables. Finally, we assess the relation between the regime probabilities and the scored points by means of Vector Auto
Regressive (VAR)models. We carry out the proposed procedure using real data and, in the analyzed case studies, we find that structural changes
are strongly associated to offensive and defensive game phases and that there is some association between the surface area dynamics and the points
scored by the team and the opponent.
Research Interests:
To assess the scoring probability of teams and players in different areas of a court map is an important topic in basketball analytics, in order to define both game strategies and training programmes. In this contribution we propose a... more
To assess the scoring probability of teams and players in different areas of a
court map is an important topic in basketball analytics, in order to define both game
strategies and training programmes.
In this contribution we propose a method based on regression trees, aimed to define
a partition of the court in rectangles with maximally different scoring probabilities.
Each analysed team/player has its/his own partition, so comparisons can be made
among different teams/players. In addition, shooting efficiency measures computed
within the rectangles can be used to define spatial scoring performance indicators.
court map is an important topic in basketball analytics, in order to define both game
strategies and training programmes.
In this contribution we propose a method based on regression trees, aimed to define
a partition of the court in rectangles with maximally different scoring probabilities.
Each analysed team/player has its/his own partition, so comparisons can be made
among different teams/players. In addition, shooting efficiency measures computed
within the rectangles can be used to define spatial scoring performance indicators.
Research Interests:
In the context of Smart Cities, monitoring the dynamic of the presence of people is a crucial aspect for the well-being of an urban area. We use mobile phone data as a proxy for the total number of people (Carpita & Simonetto 2014), with... more
In the context of Smart Cities, monitoring the dynamic of the presence of
people is a crucial aspect for the well-being of an urban area. We use mobile
phone data as a proxy for the total number of people (Carpita & Simonetto
2014), with the specific aim of computing spatio-temporal region specific indicators.
Telecom Italia Mobile (TIM), which is the largest operator in Italy,
thanks to a research agreement with the Statistical Office of the Municipality
of Brescia, provided to us about two years (April 2014 to June 2016) of High-
Frequency Daily Mobile Phone Density Profiles (DMPDPs) in the form of a
regular grid polygon each 15 minutes. Densities have to be rescaled in order
to express the total amount of people rather than just TIM users. Separately
for selected regions in the province of Brescia, characterized by being either
working or residential areas, we group similar DMPDPs and we characterize
groups by their spatial and temporal components. In doing so, we propose a
mixed-approach procedure. First, borrowing the method of the Histogram of
Oriented Gradients (HOG, Tomasi 2012), we perform a reduction of the DMPDPs
dimensionality computing their features extractions. With this method,
we convert a 2D spatial object into a 1D vector of data, by preserving the spatial
relationship contained in the data. Secondly, we stack in a single vector all
the HOG features of the same day and, by applying a high-dimensional cluster
analysis that accounts for the curse of dimensionality, we group days. Third,
for each group, we reshape the data in order to form a 3D array with dimension
a (quarters), b (days) and c (space), and we apply a Canonycal Polyadic
(CP) tensor decomposition (CANDECOMP/PARAFAC, Kolda & Bader 2009)
to extract three indicators related to the dynamic of the presences along the
space, the days and the quarters.
people is a crucial aspect for the well-being of an urban area. We use mobile
phone data as a proxy for the total number of people (Carpita & Simonetto
2014), with the specific aim of computing spatio-temporal region specific indicators.
Telecom Italia Mobile (TIM), which is the largest operator in Italy,
thanks to a research agreement with the Statistical Office of the Municipality
of Brescia, provided to us about two years (April 2014 to June 2016) of High-
Frequency Daily Mobile Phone Density Profiles (DMPDPs) in the form of a
regular grid polygon each 15 minutes. Densities have to be rescaled in order
to express the total amount of people rather than just TIM users. Separately
for selected regions in the province of Brescia, characterized by being either
working or residential areas, we group similar DMPDPs and we characterize
groups by their spatial and temporal components. In doing so, we propose a
mixed-approach procedure. First, borrowing the method of the Histogram of
Oriented Gradients (HOG, Tomasi 2012), we perform a reduction of the DMPDPs
dimensionality computing their features extractions. With this method,
we convert a 2D spatial object into a 1D vector of data, by preserving the spatial
relationship contained in the data. Secondly, we stack in a single vector all
the HOG features of the same day and, by applying a high-dimensional cluster
analysis that accounts for the curse of dimensionality, we group days. Third,
for each group, we reshape the data in order to form a 3D array with dimension
a (quarters), b (days) and c (space), and we apply a Canonycal Polyadic
(CP) tensor decomposition (CANDECOMP/PARAFAC, Kolda & Bader 2009)
to extract three indicators related to the dynamic of the presences along the
space, the days and the quarters.
Research Interests:
Data analytics in sports is crucial to evaluate the performance of single players and the whole team. The literature proposes a number of tools for both offence and defence scenarios. Data coming from tracking location of players, in this... more
Data analytics in sports is crucial to evaluate the performance of single
players and the whole team. The literature proposes a number of tools for both
offence and defence scenarios. Data coming from tracking location of players, in
this respect, may be used to enrich the amount of useful information. In basketball,
however, actions are interleaved with inactive periods. This paper describes
a methodological approach to automatically identify active periods during a game
and to classify them as offensive or defensive. The method is based on the application
of thresholds to players kinematic parameters, whose values undergo a “tuning”
strategy similar to Receiver Operating Characteristic curves, using a “ground truth”
extracted from the video of the games.
players and the whole team. The literature proposes a number of tools for both
offence and defence scenarios. Data coming from tracking location of players, in
this respect, may be used to enrich the amount of useful information. In basketball,
however, actions are interleaved with inactive periods. This paper describes
a methodological approach to automatically identify active periods during a game
and to classify them as offensive or defensive. The method is based on the application
of thresholds to players kinematic parameters, whose values undergo a “tuning”
strategy similar to Receiver Operating Characteristic curves, using a “ground truth”
extracted from the video of the games.
Research Interests:
Administrative data allows us to count for the number of residents. The geo-localization of people by mobile phone, by quantifying the number of people at a given moment in time, enriches the amount of useful information for “smart”... more
Administrative data allows us to count for the number of residents. The
geo-localization of people by mobile phone, by quantifying the number of people
at a given moment in time, enriches the amount of useful information for “smart”
(cities) evaluations. However, using Telecom Italia Mobile (TIM) data, we are able
to characterize the spatio-temporal dynamic of the presences in the city of just TIM
users. A strategy to estimate total presences is needed. In this paper we propose a
strategy to extrapolate the number of total people by using TIM data only. To do so,
we apply a spatial record linkage of mobile phone data with administrative archives
using the number of residents at the level of “sezione di censimento”.
geo-localization of people by mobile phone, by quantifying the number of people
at a given moment in time, enriches the amount of useful information for “smart”
(cities) evaluations. However, using Telecom Italia Mobile (TIM) data, we are able
to characterize the spatio-temporal dynamic of the presences in the city of just TIM
users. A strategy to estimate total presences is needed. In this paper we propose a
strategy to extrapolate the number of total people by using TIM data only. To do so,
we apply a spatial record linkage of mobile phone data with administrative archives
using the number of residents at the level of “sezione di censimento”.
Research Interests:
Global Positioning Systems (GPS) are nowadays intensively used in Sport Science as they permit to capture the space-time trajectories of players, with the aim to infer useful information to coaches in addition to traditional statistics.... more
Global Positioning Systems (GPS) are nowadays intensively used in Sport Science as they permit to capture the space-time trajectories of players, with the aim to infer useful information to coaches in addition to traditional statistics. In our application to basketball, we used Cluster Analysis in order to split the match in a number of separate time-periods, each identifying homogeneous spatial relations among players in the court. Results allowed us to identify differences in spacing among players, distinguish defensive or offensive actions, analyze transition probabilities from a certain group to another one.
I sistemi di posizionamento globali (GPS) sono ampiamente utilizzati in campo sportivo in quanto ci permettono di rilevare in diversi istanti temporali il posizionamento dei giocatori in campo, allo scopo di fornire indicazioni utili in ag-giunta alle statistiche tradizionali. Con un'applicazione sulla pallacanestro, utilizzi-amo una Cluster Analysis allo scopo di suddividere la partita in gruppi omogenei in termini di relazioni spaziali tra giocatori. Identifichiamo inoltre se ciascun gruppo corrisponde ad azioni di attacco o di difesa, e stimiamo le matrici di transizione che quantificano la probabilità di passaggio da un gruppo ad un'altro.
I sistemi di posizionamento globali (GPS) sono ampiamente utilizzati in campo sportivo in quanto ci permettono di rilevare in diversi istanti temporali il posizionamento dei giocatori in campo, allo scopo di fornire indicazioni utili in ag-giunta alle statistiche tradizionali. Con un'applicazione sulla pallacanestro, utilizzi-amo una Cluster Analysis allo scopo di suddividere la partita in gruppi omogenei in termini di relazioni spaziali tra giocatori. Identifichiamo inoltre se ciascun gruppo corrisponde ad azioni di attacco o di difesa, e stimiamo le matrici di transizione che quantificano la probabilità di passaggio da un gruppo ad un'altro.
Research Interests:
A new approach in team sports analysis consists in studying positioning and movements of players during the game in relation to team performance. State of the art tracking systems produce spatio-temporal traces of players that have... more
A new approach in team sports analysis consists in studying positioning and movements
of players during the game in relation to team performance. State of the art tracking systems
produce spatio-temporal traces of players that have facilitated a variety of research
aimed to extract insights from trajectories. Several methods borrowed from machine learning,
network and complex systems, geographic information system, computer vision and
statistics have been proposed. After having reviewed the state of the art in those niches
of literature aiming to extract useful information to analysts and experts in terms of relation
between players’ trajectories and team performance, this paper presents preliminary
results from analysing trajectories data and sheds light on potential future research in this
field of study. In particular, using convex hulls, we find interesting regularities in players’
movement patterns
of players during the game in relation to team performance. State of the art tracking systems
produce spatio-temporal traces of players that have facilitated a variety of research
aimed to extract insights from trajectories. Several methods borrowed from machine learning,
network and complex systems, geographic information system, computer vision and
statistics have been proposed. After having reviewed the state of the art in those niches
of literature aiming to extract useful information to analysts and experts in terms of relation
between players’ trajectories and team performance, this paper presents preliminary
results from analysing trajectories data and sheds light on potential future research in this
field of study. In particular, using convex hulls, we find interesting regularities in players’
movement patterns
Research Interests:
"Che cos’è L’ACQUA VIRTUALE? E’ l’acqua che non beviamo, ma che consumiamo perché viene utilizzata per produrre il cibo che mangiamo! Al giorno d’oggi stiamo vivendo, magari senza accorgercene, in un mondo globalizzato nel quale il... more
"Che cos’è L’ACQUA VIRTUALE? E’ l’acqua che non beviamo, ma che consumiamo perché viene utilizzata per produrre il cibo che mangiamo!
Al giorno d’oggi stiamo vivendo, magari senza accorgercene, in un mondo globalizzato nel quale il fabbisogno energetico della popolazione mondiale è intimamente legata alla disponibilità di acqua.
Forse ci aspetteremmo di consumare solo l’acqua che beviamo (uno o due litri al giorno), invece le cifre che la FAO ci propone riguardante l’acqua che inconsapevolmente consumiamo sono del tutto diverse: Ogni prodotto che noi consumiamo necessità di tanta acqua affinchè esso sia prodotto. Occorrono infatti più di 1.000 litri d'acqua virtuale per produrre un chilo di grano, e circa 14.000 litri di acqua virtuale per ottenere un chilo di carne. Alla fine dei conti, ognuno di noi consuma mediamente 2.000 litri di acqua virtuale al giorno.
Provate a calcolare il consumo annuale moltiplicando per 365, il risultato è sorprendente: 730 mila litri di acqua per ogni persona. Basta sommare gli 87 mila abitanti di Lucca per ottenere un numero difficile da pronunciare!
Tuttavia, come è facile pensare, la disponibilità di acqua è limitata, soprattutto in certe aree calde e desertiche, cosicchè diventa necessario il commercio internazionale di acqua e di prodotti che contengono acqua, al fine di garantire il sostentamento di tutti noi.
Ma come avviene il commercio di acqua? Ci sono o meno delle dinamiche che dirottano l’acqua verso i paesi più ricchi a discapito dei paesi poveri? Come può essere reso più efficiente? E come si inserisce in tutto questo la discussione relativa alla privatizzazione dell’acqua, che è già una commodity in Australia? E come influisce il cambiamento climatico? Infine, cosa possiamo fare, ciascuno di noi, per ridurre il consumo di acqua? … sono alcune delle domande che ci poniamo.
"
Al giorno d’oggi stiamo vivendo, magari senza accorgercene, in un mondo globalizzato nel quale il fabbisogno energetico della popolazione mondiale è intimamente legata alla disponibilità di acqua.
Forse ci aspetteremmo di consumare solo l’acqua che beviamo (uno o due litri al giorno), invece le cifre che la FAO ci propone riguardante l’acqua che inconsapevolmente consumiamo sono del tutto diverse: Ogni prodotto che noi consumiamo necessità di tanta acqua affinchè esso sia prodotto. Occorrono infatti più di 1.000 litri d'acqua virtuale per produrre un chilo di grano, e circa 14.000 litri di acqua virtuale per ottenere un chilo di carne. Alla fine dei conti, ognuno di noi consuma mediamente 2.000 litri di acqua virtuale al giorno.
Provate a calcolare il consumo annuale moltiplicando per 365, il risultato è sorprendente: 730 mila litri di acqua per ogni persona. Basta sommare gli 87 mila abitanti di Lucca per ottenere un numero difficile da pronunciare!
Tuttavia, come è facile pensare, la disponibilità di acqua è limitata, soprattutto in certe aree calde e desertiche, cosicchè diventa necessario il commercio internazionale di acqua e di prodotti che contengono acqua, al fine di garantire il sostentamento di tutti noi.
Ma come avviene il commercio di acqua? Ci sono o meno delle dinamiche che dirottano l’acqua verso i paesi più ricchi a discapito dei paesi poveri? Come può essere reso più efficiente? E come si inserisce in tutto questo la discussione relativa alla privatizzazione dell’acqua, che è già una commodity in Australia? E come influisce il cambiamento climatico? Infine, cosa possiamo fare, ciascuno di noi, per ridurre il consumo di acqua? … sono alcune delle domande che ci poniamo.
"
Research Interests:
MOTIVATION /CONTRIBUTIONS Eigenvector spatial filtering (SF) variants of the Poisson/NegBin specification have been proposed in the literature of gravity of trade to accommodate spatial autocorrelation. Two contributions: 1)We employ a... more
MOTIVATION /CONTRIBUTIONS Eigenvector spatial filtering (SF) variants of the Poisson/NegBin specification have been proposed in the literature of gravity of trade to accommodate spatial autocorrelation. Two contributions: 1)We employ a stepwise selection criterion applied to spatial filters only. This is based on robust (sandwich) p-values and does not require likelihood-based indicators. 2)We use the selected spatial filters to properly account for importer-and exporter-side specific spatial effects, and differently for the count and logit parts of zero-inflated Poisson and negative binomial models.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Floods are one of the natural disasters which cause the worst human, social and economic impacts to the detriment of both public and private sectors. Today, public decision-makers can take advantage of the availability of data-driven... more
Floods are one of the natural disasters which cause the worst human, social and economic impacts to the detriment of both public and private sectors. Today, public decision-makers can take advantage of the availability of data-driven systems that allow to monitor hydrogeological risk areas and that can be used for predictive purposes to deal with future emergency situations. Flooding risk exposure maps traditionally assume amount of presences constant over time, although crowding is a highly dynamic process in metropolitan areas. Real-time monitoring and forecasting of people’s presences and mobility is thus a relevant aspect for metropolitan areas subjected to flooding risk. In this respect, mobile phone network data have been used with the aim of obtaining dynamic measure for the exposure risk in areas with hydrogeological criticality. In this work, we use mobile phone origin-destination signals on traffic flows by Telecom Italia Mobile (TIM) users with the aim of forecasting the ...
Research Interests:
The use of new sources of big data collected at a high-frequency rate in conjunction with administrative data is critical to developing indicators of the exposure to risks of small urban areas. Correctly accounting for the crowding of... more
The use of new sources of big data collected at a high-frequency rate in conjunction with administrative data is critical to developing indicators of the exposure to risks of small urban areas. Correctly accounting for the crowding of people and for their movements is crucial to mitigate the effect of natural disasters, while guaranteeing the quality of life in a “smart city” approach. We use two different types of mobile phone data to estimate people crowding and traffic intensity. We analyze the temporal dynamics of crowding and traffic using a Model-Based Functional Cluster Analysis, and their spatial dynamics using the T-mode Principal Component Analysis. Then, we propose five indicators useful for risk management in small urban areas: two composite indicators based on cutting-edge mobile phone dynamic data and three indicators based on open-source street map static data. A case study for the flood-prone area of the Mandolossa (the western outskirts of the city of Brescia, Italy...
Research Interests:
Research Interests:
Multi-regional input–output (I/O) matrices provide the networks of within- and cross-country economic relations. In the context of I/O analysis, the methodology adopted by national statistical offices in data collection raises the issue... more
Multi-regional input–output (I/O) matrices provide the networks of within- and cross-country economic relations. In the context of I/O analysis, the methodology adopted by national statistical offices in data collection raises the issue of obtaining reliable data in a timely fashion and it makes the reconstruction of (parts of) the I/O matrices of particular interest. In this work, we propose a method combining hierarchical clustering and matrix completion with a LASSO-like nuclear norm penalty, to predict missing entries of a partially unknown I/O matrix. Through analyses based on both real-world and synthetic I/O matrices, we study the effectiveness of the proposed method to predict missing values from both previous years data and current data related to countries similar to the one for which current data are obscured. To show the usefulness of our method, an application based on World Input–Output Database (WIOD) tables—which are an example of industry-by-industry I/O tables—is p...
Research Interests:
Research Interests:
Research Interests:
To assess the scoring probability of teams and players in different areas of a court map is an important topic in basketball analytics, in order to define both game strategies and training programmes. In this contribution we propose a... more
To assess the scoring probability of teams and players in different areas of a court map is an important topic in basketball analytics, in order to define both game strategies and training programmes. In this contribution we propose a method based on regression trees, aimed to define a partition of the court in rectangles with maximally different scoring probabilities. Each analysed team/player has its/his own partition, so comparisons can be made among different teams/players. In addition, shooting efficiency measures computed within the rectangles can be used to define spatial scoring performance indicators.
Research Interests:
In the context of Smart Cities, monitoring the dynamic of the presence of people is a crucial aspect for the well-being of an urban area. We use mobile phone data as a proxy for the total number of people (Carpita & Simonetto... more
In the context of Smart Cities, monitoring the dynamic of the presence of people is a crucial aspect for the well-being of an urban area. We use mobile phone data as a proxy for the total number of people (Carpita & Simonetto 2014), with the specific aim of computing spatio-temporal region specific indicators. Telecom Italia Mobile (TIM), which is the largest operator in Italy, thanks to a research agreement with the Statistical Office of the Municipality of Brescia, provided to us about two years (April 2014 to June 2016) of High-Frequency Daily Mobile Phone Density Profiles (DMPDPs) in the form of a regular grid polygon each 15 minutes. Densities have to be rescaled in order to express the total amount of people rather than just TIM users. Separately for selected regions in the province of Brescia, characterized by being either working or residential areas, we group similar DMPDPs and we characterize groups by their spatial and temporal components. In doing so, we propose a mixed-approach procedure.
Research Interests:
Research Interests:
In the context of Smart cities, local institutions face the increasing need for monitoring the dynamic of the flow of people’s presences inside urban areas in order to plan the improvement and the maintaining of the urban infrastructure.... more
In the context of Smart cities, local institutions face the increasing need for monitoring the dynamic of the flow of people’s presences inside urban areas in order to plan the improvement and the maintaining of the urban infrastructure. Rectangular grid polygons reporting the density of people using mobile phone (Carpita, Simonetto, 2014) are source of very large data. Telecom Italia Mobile (TIM), which is currently the largest operator in Italy in this sector, thanks to a research agreement with the Statistical Office of the Municipality of Brescia, provided to us about two years (April 2014 to June 2016, n about 700) of Daily Mobile Phone Density Profiles (DMPDPs) for the Province of Brescia in the form of a regular grid of 923 x 607 cells each 15 minutes. In order to find regularities and detect anomalies in the flow of people’s presences, this work aims to cluster similar DMPDPs, where each DMPDP is characterized by both the 2-D spatial component (i.e. 923 x 607 dimensions, one...
Research Interests:
<jats:p xml:lang="en">The analysis of origin-destination traffic flows may be useful in many contexts of application (e.g., urban planning, tourism economics) and have been commonly studied through the gravity model, which... more
<jats:p xml:lang="en">The analysis of origin-destination traffic flows may be useful in many contexts of application (e.g., urban planning, tourism economics) and have been commonly studied through the gravity model, which states that flows are proportional to ''masses" of both origin and destination, and inversely proportional to distance between them. Using data on the flow of mobile phone SIM among different aree di censimento, recorded hourly basis for several months and provided by FasterNet in the context of MoSoRe project, in this work we characterize and model the dynamic of such flows over the time in the strongly urbanized and flood-prone area of the Mandolossa (western outskirts of Brescia, northern Italy), with the aim of predicting the traffic flow during flood episodes. Whereas a traditional "static" mass explanatory variable is represented by residential population (Pop), or by gross domestic product (GDP), here we propose to use a most accurate set of explanatory variables in order to better account for the dynamic over the time. First, we employ a time-varying mass variable represented by the number of city-users by area and by time period, which has been estimated from mobile phone data (provided by TIM) using functional data approach and already adopted to derive crowding maps for flood exposure. Secondly, we include in the model a proper set of factors such as areal and time dummies, and a novel set of indices related to (e.g.) the number and the type of streets, the number of offices, restaurants or cinemas, which may be retrieved from OpenStreetMap. The joint use of these two novel sets of explanatory variables should allow us to obtain a better linear fitting of the gravity model and a better traffic flow prediction for the flood risk evaluation.</jats:p>
This work is copyrighted by Università del Salento, and is licensed under a Creative Commons Attribuzione-Non commerciale-Non opere derivate 3.0 Italia License. For more information see:... more
This work is copyrighted by Università del Salento, and is licensed under a Creative Commons Attribuzione-Non commerciale-Non opere derivate 3.0 Italia License. For more information see: http://creativecommons.org/licenses/by-nc-nd/3.0/it/ A new approach to performance analysis in team sports consists in studying movements and trajectories of players during the game. State of the art tracking systems produce spatio-temporal traces of players that have facilitated a variety of research aimed to to extract insight from trajectories. Several methods borrowed from machine learning, network and complex systems , geographic information system, computer vision and statistics have been proposed. However, the use of an effective and easy-to-use visual tool in support to these methods is of major importance. To this scope this paper suggests the use of motion charts, built by means of the open-source gvisMotionChart function in googleVis package in R, a user-friendly procedure that also allow...
Research Interests:
Research Interests:
Research Interests:
Global Positioning Systems (GPS) are nowadays intensively used in Sport Science as they permit to capture the space-time trajectories of players, with the aim to infer useful information to coaches in addition to traditional statistics.... more
Global Positioning Systems (GPS) are nowadays intensively used in Sport Science as they permit to capture the space-time trajectories of players, with the aim to infer useful information to coaches in addition to traditional statistics. In our application to basketball, we used Cluster Analysis in order to split the match in a number of separate time-periods, each identifying homogeneous spatial relations among players in the court. Results allowed us to identify differences in spacing among players, distinguish defensive or offensive actions, analyze transition probabilities from a certain group to another one.
Research Interests:
In the context of Smart City, the dynamic of the presence of people can be analysed using high-dimensional spatio-temporal mobile phone data. In order to find regularities and detect anomalies in the daily profiles, we propose an approach... more
In the context of Smart City, the dynamic of the presence of people can be analysed using high-dimensional spatio-temporal mobile phone data. In order to find regularities and detect anomalies in the daily profiles, we propose an approach that considers the spatial structure by means of Histogram of Oriented Gradients (HOG) method and the temporal evolution using a Model-Based Clustering Functional Data Analysis (FDA). An application to the case study of the Municipality of Brescia is provided. Similarities among days, that follow a seasonal or a days of the week trend, exist. The number of users in the city, depending on the season, the day of the week and the time of the day, varies from 30 to 60 thousands of people
Research Interests:
Data analytics in sports is crucial to evaluate the performance of single players and the whole team. The literature proposes a number of tools for both offence and defence scenarios. Data coming from tracking location of players, in this... more
Data analytics in sports is crucial to evaluate the performance of single players and the whole team. The literature proposes a number of tools for both offence and defence scenarios. Data coming from tracking location of players, in this respect, may be used to enrich the amount of useful information. In basketball, however, actions are interleaved with inactive periods. This paper describes a methodological approach to automatically identify active periods during a game and to classify them as offensive or defensive. The method is based on the application of thresholds to players kinematic parameters, whose values undergo a tuning strategy similar to Receiver Operating Characteristic curves, using a ground truth extracted from the video of the games.
Research Interests:
Administrative data allows us to count for the number of residents. The geo-localization of people by mobile phone, by quantifying the number of people at a given moment in time, enriches the amount of useful information for... more
Administrative data allows us to count for the number of residents. The geo-localization of people by mobile phone, by quantifying the number of people at a given moment in time, enriches the amount of useful information for "smart" (cities) evaluations. However, using Telecom Italia Mobile (TIM) data, we are able to characterize the spatio-temporal dynamic of the presences in the city of just TIM users. A strategy to estimate total presences is needed. In this paper we propose a strategy to extrapolate the number of total people by using TIM data only. To do so, we apply a spatial record linkage of mobile phone data with administrative archives using the number of residents at the level of sezione di censimento.
Research Interests:
In the domain of Sport Analytics, Global Positioning Systems devices are intensively used as they permit to retrieve players' movements. Team sports' managers and coaches are interested on the relation between players'... more
In the domain of Sport Analytics, Global Positioning Systems devices are intensively used as they permit to retrieve players' movements. Team sports' managers and coaches are interested on the relation between players' patterns of movements and team performance, in order to better manage their team. In this paper we propose a Cluster Analysis and Multidimensional Scaling approach to find and describe separate patterns of players movements. Using real data of multiple professional basketball teams, we find, consistently over different case studies, that in the defensive clusters players are close one to another while the transition cluster are characterized by a large space among them. Moreover, we find the pattern of players' positioning that produce the best shooting performance.ment and we match them with play-by-play, to find successful strategies.
Research Interests:
Big Data Analytics help team sports' managers in their decisions by processing a number of different kind of data. With the advent of Information Technologies, collecting, processing and storing big amounts of sport data in different... more
Big Data Analytics help team sports' managers in their decisions by processing a number of different kind of data. With the advent of Information Technologies, collecting, processing and storing big amounts of sport data in different form became possible. A problem that often arises when using sport data regards the need for automatic data cleaning procedures. In this paper we develop a data cleaning procedure for basketball which is based on players' trajectories. Starting from a data matrix that tracks the movements of the players on the court at different moments in the game, we propose an algorithm to automatically drop inactive moments making use of available sensor data. The algorithm also divides the game into sorted actions and labels them as offensive or defensive. The algorithm's parameters are validated using proper robustness checks.
Research Interests:
Basketball players' performance measurement is of critical importance for a broad spectrum of decisions related to training and game strategy. Despite this recognized central role, the main part of the studies on this topic focus on... more
Basketball players' performance measurement is of critical importance for a broad spectrum of decisions related to training and game strategy. Despite this recognized central role, the main part of the studies on this topic focus on performance level measurement, neglecting other important characteristics, such as variability. In this paper, shooting performance variability is modeled with a Markov Switching dynamic, assuming the existence of two alternating performance regimes. Then, the relationships between each player's variability and the lineup composition is modeled as an ARIMA process with covariates and described with network analysis tools, in order to extrapolate positive and negative interactions between teammates
Research Interests:
A new approach in team sports analysis consists in studying positioning and movements of players during the game in relation to team performance. State of the art tracking systems produce spatio-temporal traces of players that have... more
A new approach in team sports analysis consists in studying positioning and movements of players during the game in relation to team performance. State of the art tracking systems produce spatio-temporal traces of players that have facilitated a variety of research aimed to extract insights from trajectories. Several methods borrowed from machine learning, network and complex systems, geographic information system, computer vision and statistics have been proposed. After having reviewed the state of the art in those niches of literature aiming to extract useful information to analysts and experts in terms of relation between players' trajectories and team performance, this paper presents preliminary results from analysing trajectories data and sheds light on potential future research in this field of study. In particular, using convex hulls, we find interesting regularities in players' movement patterns.
Research Interests:
In the domain of Sport Analytics, Global Positioning Systems devices are intensively used as they permit to retrieve players' movements. Team sports' managers and coaches are interested on the relation between players'... more
In the domain of Sport Analytics, Global Positioning Systems devices are intensively used as they permit to retrieve players' movements. Team sports' managers and coaches are interested on the relation between players' patterns of movements and team performance, in order to better manage their team. In this paper we propose a Cluster Analysis and Multidimensional Scaling approach to find and describe separate patterns of players movements. Using real data of multiple professional basketball teams, we find, consistently over different case studies, that in the defensive clusters players are close one to another while the transition cluster are characterized by a large space among them. Moreover, we find the pattern of players' positioning that produce the best shooting performance.
Research Interests:
Research Interests:
Research Interests:
To know the number of city users is essential since it provides a big amount of useful information in the context of Smart City evaluations that traditional static measures—represented by the number of residents from census data—are not... more
To know the number of city users is essential since it provides a big amount of useful information in the context of Smart City evaluations that traditional static measures—represented by the number of residents from census data—are not able to provide. In this paper we use spatiotemporal mobile phone data along with administrative data to develop a dynamic indicator for the number of city users. In doing so, we propose a multi-stage approach for high-dimensional data, that, in the first part, it permits to estimate the number of phone company users for different reference days by means of an approach based on Histogram of Oriented Gradients for data dimensionality reduction, and by means of a mix of k-means and Functional Data Analysis Model-Based Clustering methods for clustering days. The second part is aimed at employing a method—based on matching mobile phone and administrative data—to estimate the phone company market share at small area level, which is used to derive city users. Applying the method to the case study of the Municipality of Brescia, we find that our estimated market share outperforms the national level counterpart. Moreover, we find that the number of city users reaches a peak of 270–280 thousand during the central hours of autumn to spring weekdays.
Research Interests:
Measuring players' performance in team sports is fundamental since managers need to evaluate players with respect to the ability to score during crucial moments of the game. Using Classification and Regression Trees (CART) and... more
Measuring players' performance in team sports is fundamental since managers need to evaluate players with respect to the ability to score during crucial moments of the game. Using Classification and Regression Trees (CART) and play-by-play basketball data, we estimate the probabilities to score the shot with respect to a selection of game covariates related to game pressure. We use scoring probabilities to develop a player-specific shooting performance index that takes into account for the difficulty associated to score different types of shots. By applying this procedure to a large sample of 2016–2017 Basketball Champions League (BCL) and 2017–2018 National Basketball Association (NBA) games, we compare the factors affecting shooting performance in Europe and in the United States and we evaluate a selection of players in terms of the proposed shooting performance index with the final aim of providing useful guidelines for the team strategy.
Research Interests:
Because of the advent of GPS techniques, a wide range of scientific literature on Sport Science is nowadays devoted to the analysis of players’ movement in relation to team performance in the context of big data analytics. A specific... more
Because of the advent of GPS techniques, a wide range of scientific literature on Sport Science is nowadays devoted to the analysis of players’ movement in relation to team performance in the context of big data analytics. A specific research question regards whether certain patterns of space among players affect team performance, from both an offensive and a defensive perspective. Using a time series of basketball players’ coordinates, we focus on the dynamics of the surface area of the five players on the court with a two-fold purpose: (i) to give tools allowing a detailed description and analysis of a game with respect to surface areas dynamics and (ii) to investigate its influence on the points made by both the team and the opponent. We propose a three-step procedure integrating different statistical modelling approaches. Specifically, we first employ a Markov Switching Model (MSM) to detect structural changes in the surface area. Then, we perform descriptive analyses in order t...
Research Interests:
Research Interests:
This paper investigates the relationship between international trade and migration with the specific aim of estimating direct and indirect effect of the latter on cross-border flows of both homogeneous and differentiated goods. Adopting a... more
This paper investigates the relationship between international trade and migration with the specific aim of estimating direct and indirect effect of the latter on cross-border flows of both homogeneous and differentiated goods. Adopting a spatial econometric approach along with a gravity model set-up, we account for the role of ethnic communities in neighbouring countries on trade, and we propose a new way to define neighbours based on the intensity of links in the migration network. Our approach is particularly well suited to measure the indirect effect stemming from the presence of significant ethnic communities on trade through a “market familiarization” effect. Using data covering all countries between 1970 and 2000, we find a significant indirect effect of migration on trade, that depends on the chosen weight matrix.
Research Interests:
Research Interests:
Research Interests: Business, Environmental Engineering, Civil Engineering, Water, International Trade, and 12 moreWater resources, Oil and gas, Water Conflicts, Social Science Research Network, Gravity Model, Trade Openness, Virtual Water, Water scarcity, Militarized Interstate Disputes, Rare Events, Virtual Water and Water Footprint, and Elsevier
Bilateral trade flows traditionally have been analysed by means of the spatial interaction gravity model. Still, (auto)correlation of trade flows has only recently received attention in the literature. This paper takes up this thread of... more
Bilateral trade flows traditionally have been analysed by means of the spatial interaction gravity model. Still, (auto)correlation of trade flows has only recently received attention in the literature. This paper takes up this thread of emerging literature, and shows that spatial filtering (SF) techniques can take into account the autocorrelation in trade flows. Furthermore, we show that the use of origin and destination specific spatial filters goes a long way in correcting for omitted variable bias in an otherwise standard empirical gravity equation. For a cross-section of bilateral trade flows, we compare an SF approach to two benchmark specifications that are consistent with theoretically derived gravity. The results are relevant for a number of reasons. First, we correct for autocorrelation in the residuals. Second, we suggest that the empirical gravity equation can still be considered in applied work, despite the theoretical arguments for its misspecification due to omitted multilateral resistance terms. Third, if we include SF variables, we can still resort to any desired estimator, such as OLS, Poisson or negative binomial regression. Finally, interpreting endogeneity bias as autocorrelation in regressor variables and residuals allows for a more general specification of the gravity equation than the relatively restricted theoretical gravity equation. In particular, we can include additional country-specific push and pull variables, besides GDP (e.g., land area, landlockedness, and per capita GDP). A final analysis provides autocorrelation diagnostics according to different candidate indicators.
Research Interests:
Disentangling the relations between human migrations and water resources is relevant for food security and trade policy in water-scarce countries. It is commonly believed that human migrations are beneficial to the water endowments of... more
Disentangling the relations between human migrations and water resources is relevant for food security and trade policy in water-scarce countries. It is commonly believed that human migrations are beneficial to the water endowments of origin countries for reducing the pressure on local resources. We show here that such belief is over-simplistic. We reframe the problem by considering the international food trade and the corresponding virtual water fluxes, which quantify the water used for the production of traded agricultural commodities. By means of robust analytical tools, we show that migrants strengthen the commercial links between countries, triggering trade fluxes caused by food consumption habits persisting after migration. Thus migrants significantly increase the virtual water fluxes and the use of water in the countries of origin. The flux ascribable to each migrant, i.e. the "water suitcase", is found to have increased from 321 m3/y in 1990 to 1367 m3/y in 2010. A...