Data Science for Sports Analytics

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Sports analytics have evolved in recent years in an amazing way, thanks to automated or semi-automated sensing technologies that provide high-fidelity data streams extracted from every game. In the lab we are investigating data-driven approaches to boost the understanding of sports performance, in two main context: cycling and football..
Manager: 
Pappalardo, L., P. Cintia, P. Ferragina, E. Massucco, D. Pedreschi, and F. Giannotti, "PlayeRank: data-driven performance evaluation and player ranking in soccer via a machine learning approach", ACM Transactions on Intelligent Systems and Technology (TIST), vol. 10, no. 5, pp. 1–27, 2019.
Cintia, P., L. Pappalardo, D. Pedreschi, F. Giannotti, and M. Malvaldi, "The harsh rule of the goals: data-driven performance indicators for football teams", IEEE International Conference on Data Science and Advanced Analytics, 2015.
Cintia, P., L. Pappalardo, and D. Pedreschi, "Mining efficient training patterns of non-professional cyclists", 22nd Italian Symposium on Advanced Database Systems, {SEBD} 2014, Sorrento Coast, Italy, June 16-18, 2014., 2014.
Cintia, P., L. Pappalardo, and D. Pedreschi, ""Engine Matters": {A} First Large Scale Data Driven Study on Cyclists' Performance", 13th {IEEE} International Conference on Data Mining Workshops, {ICDM} Workshops, TX, USA, December 7-10, 2013, 2013.

Player rank: performance evaluation for soccer players

Paolo Cintia introduces the PlayerRank system used to learn and rank football players.

Exploring football match events in Python

An entry level video on football analytics in Python. Luca Pappalardo talks through:

Luca Pappalardo has been interviewed by SuperQuark Piu' (RaiPlay) about the status of research in Sports Analytics.

The largest collection ever of spatio-temporal data of soccer matches is made public on Scientific Data. A crucial resource for the developing of Sports Analytics.

Soccer & Data Cup - Genova

Dal 4 al 6 aprile si e' svolto a Genova il primo torneo di calcio & dati nella cornice dell'evento Futura 2019 organizzato dal MIUR.

Radio Aula 40 17 Novembre 2016

Paolo Cintia and Luca Pappalardo have joined the conversation on sports at Radio Aula 40 talking about sports analytics.

Big Data applied to soccer: Paolo Cintia and Luca Pappalardo are interviewed by Zona Cesarini, a sport program on Rai Radio 1, the Italian national radio broadcasting network.

Paolo Cintia and Luca Pappalardo interviewed by Radio 3 Scienza on the italian national broadcasting network Rai Radio 3.

Un computer a disposizione di un allenatore era un’utopia, nel 1973. La storia dei dati e del calcolo applicato al calcio non poteva che cominciare in un posto dove di utopia, nel 1973, se ne intendevano: l’Unione Sovietica.

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Image by Charis Tsevis CC NC-ND 2.0, via Flickr
Acronym
DSSA
Start Date
1 June 2013
Type
Internal Project
Area
Affiliation
Department of Computer Science, University of Pisa (DI-UNIPI)