Data Science for Sports Analytics

The Data Science for Sports Analytics group has a multidisciplinary background, i.e. machine learning technique, big data analysis and sports science. The main topics of this group involve the development of models in sports and in particular in soccer that permits to deeply assess the sport performance both in physical demands and technical-tactical performances.

Image by Charis Tsevis CC NC-ND 2.0, via Flickr

Web page

https://kdd.isti.cnr.it/project/data-science-sports-analytics 

Members

Paolo Cintia

Paolo Cintia

PostDoc

Luca Pappalardo

Luca Pappalardo

Researcher @CNR

Alessio Rossi

Alessio Rossi

PostDoc

Projects

SoBigData++

2021.

(Abstract | Links)

SoBigData++ strives to deliver a distributed, Pan-European, multi-disciplinary research infrastructure for big social data analytics, coupled with the consolidation of a cross-disciplinary European research community, aimed at using social mining and big data to understand the complexity of our contemporary, globally-interconnected society. SoBigData++ will move forward from a starting community of pioneers to a wide and diverse scientific movement, capable of empowering the next generation of responsible social data scientists, engaged in the grand societal challenges laid out in its exploratories: Societal Debates and Online Misinformation, Sustainable Cities for Citizens, Demography, Economics & Finance 2.0, Migration Studies, Sports Data Science, Social Impact of Artificial Intelligence and Explainable Machine Learning. In particular, the exploratory on Sports Data Science focuses on research related to sports and health analytics.

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Selected Publications

2019

Pappalardo, Luca; Cintia, Paolo; Ferragina, Paolo; Massucco, Emanuele; Pedreschi, Dino; Giannotti, Fosca

PlayeRank: Data-driven Performance Evaluation and Player Ranking in Soccer via a Machine Learning Approach Journal Article

In: ACM Transactions on Intelligent Systems and Technology, vol. 10, no. 5, pp. 1–27, 2019.

Links | BibTeX

Morelli, Davide; Rossi, Alessio; Cairo, Massimo; Clifton, David A

Analysis of the Impact of Interpolation Methods of Missing RR-intervals Caused by Motion Artifacts on HRV Features Estimations Journal Article

In: Sensors, vol. 19, no. 14, pp. 3163, 2019.

Links | BibTeX

Rossi, Alessio; Perri, Enrico; Pappalardo, Luca; Cintia, Paolo; Iaia, Fedon Marcello

Relationship between External and Internal Workloads in Elite Soccer Players: Comparison between Rate of Perceived Exertion and Training Load Journal Article

In: Applied Sciences, vol. 9, no. 23, pp. 5174, 2019.

Links | BibTeX

Pappalardo, Luca; Cintia, Paolo; Rossi, Alessio; Massucco, Emanuele; Ferragina, Paolo; Pedreschi, Dino; Giannotti, Fosca

A public data set of spatio-temporal match events in soccer competitions Journal Article

In: Scientific Data, vol. 6, no. 1, 2019.

Links | BibTeX

2018

Rossi, Alessio; Pappalardo, Luca; Cintia, Paolo; Iaia, Fedon Marcello; Fernandez, Javier; Medina, Daniel

Effective injury forecasting in soccer with GPS training data and machine learning Journal Article

In: PLOS ONE, vol. 13, no. 7, pp. e0201264, 2018.

Links | BibTeX