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I soci fondatori di PlayeRank operano nel settore della Sports Analytics dal 2013 con risultati scientifici pubblicati su prestigiose riviste e conferenze internazionali, relativi al ciclismo, al rugby e soprattutto al calcio. Questi risultati scientifici sono stati sovente oggetto di attenzione da parte di quotidiani nazionali e internazionali (Corriere della Sera, Espresso, Forbes, Il Foglio, Il Sole24ore, PhysicsWorld.com, MIT Technology Review, TuttoSport, Wired), di media nazionali (RAI Radio1, RAI Radio3 Scienza), e hanno originato collaborazioni con diverse società di calcio professionistiche (FC Barcelona, AS Roma, FC Inter e Ferencváros) e con prestigiose università europee (Fraunhofer Institut di Bonn, Central European University di Budapest) e americane (Harvard University e Northeastern University di Boston). Questi studi sono stati finanziati anche con i fondi di un progetto europeo H2020 “SoBigData: Social Mining & Big Data Ecosystem” (INFRAIA-1-2014-2015, agreement #654024) in cui il CNR di Pisa è coordinatore e vede la partecipazione dell’Università di Pisa e di varie altre università europee provenienti da sette Paesi.

I soci fondatori di PlayeRank hanno organizzato numerosi eventi sul tema Sports Analytics all’interno di importanti manifestazioni italiane e internazionali, quali l’Internet Festival (Pisa, 2015 e 2016), il Festival della Robotica (Pisa, 2017 e 2018), la conferenza internazionale sulla Network Science (Parigi, 2018 e Indianapolis, 2017), la conferenza internazionale sul Data Mining (Barcellona, 2016 e New Orleans, 2017). Numerose sono inoltre le loro partecipazioni ad eventi sul tema Soccer Analytics, quali la “Chiusura del Calcio Mercato” (Milano, 2017), l’Hackathon del calcio organizzato dalla FIGC (Trento, 2017), il forum degli allievi della Scuola Normale Superiore (Pisa, 2018), la conferenza internazionale sul linguaggio Python (Firenze, 2018), la Festa della Rete (Rimini, 2015), il Football Fest (Perugia, 2015), conferenze organizzate dal CONI (Roma, 2017), lo Sports Technology Symposium (Barcellona, 2015), la conferenza internazionale sulla Network Science (Seul, 2016).

Alcuni articoli scientifici pubblicati dal Team sul tema Sports Analytics:

  1. P. Cintia, L. Pappalardo, D. Pedreschi, “Engine matters:  a first large scale data driven study on cyclists’ performance”, Proceedings of the IEEE 13th International Conference on Data Mining (ICDM 2013) Workshops, 2013.
  2. P. Cintia, M. Coscia, L. Pappalardo, “The Haka network: Evaluating rugby team performance with dynamic graph analysis”,  2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2016.
  3. L. Pappalardo, P. Cintia, “Quantifying the relation between performance and success in soccer”, Advances in Complex Systems, 20 (4), 2017.
  4. A. Rossi, L. Pappalardo, P. Cintia, J. Fernandez, M. F. Iaia, D. Medina, “Who is going to get hurt? Predicting injuries in professional soccer”, In Proceedings of the Machine Learning and Data Mining for Sports Analytics workshop (MLSA’17), ECML/PKDD 2017, Skopje, Macedonia, 2017.
  5. P. Cintia, L. Pappalardo, D. Pedreschi, F. Giannotti, M. Malvaldi, “The harsh rule of the goals: data-driven performance indicators for football teams”, In Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA’2015), Paris, France, 2015.
  6. P. Cintia, S. Rinzivillo and L. Pappalardo, “A network-based approach to evaluate the performance of football teams”, In Proceedings of the Machine Learning and Data Mining for Sports Analytics workshop (MLSA’15), ECML/PKDD 2015, Porto, Portugal, 2015.
  7. L. Pappalardo, P. Cintia, P. Ferragina, E. Massucco, D. Pedreschi, F. Giannotti, “Multi-dimensional and role-aware rating of soccer player performance”, In arXiv 1802.04987, February 2018.
  8. L. Pappalardo, P. Cintia, D. Pedreschi, F. Giannotti, A.-L. Barabasi, Human Perception of Performance, In  arXiv 1712.02224, December 2017.
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