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TDDE64 Sports Analytics

Timetable


  • March 31, 2025, 10:15-12:00, R6, Introduction (Patrick Lambrix)
  • April 1, 2025, 13:15-15:00, A302, Ice Hockey Analytics research at IDA (Patrick Lambrix)
  • April 14, 2025, 10:15-12:00, R34, Football and Basketball Analytics research at IDA (Patrick Lambrix)
  • April 15, 2025, 13:15-15:00, R27, Hockey Analytics (Mikael Vernblom, Linköping Hockey Club)
  • April 25, 2025, 15:15-17:00, R6, Football analytics (Pegah Rahimian, Uppsala University)
  • April 29, 2025, 13:15-15:00, R34, Baseball Analytics (Marcus Bendtsen, LiU)
  • May 5, 2025, 10:15-12:00, R42 + online, Football Analytics at Playmaker AI (Jesper Haglöf, Playmaker AI)
  • May 20, 2025, 13:15-17:00, S10, student presentations
    football: Abbas (*), Abuzar(*), Alexander (*), Haoran/Zekai (*), Kairui (*), Mehmet (*), Ramon (*), Sabrina (*)
  • May 22, 2025, 8:15-10:00, P36, student presentations
    basketball: Jeganathan (*), Thor (*)
    ice hockey: Jacob (*), (Ludwig/)Matteus (*)
  • May 23, 2025, 15:15-17:00, S10, student presentation
    cricket: Karthik (*), Md Bokhtiar/Minhas
    e-sports: Amir (*)
    American football: Elin/Todel (*)
Student presentations
  • (American football) Elin, Todel: Eager et al. Using Tracking and Charting Data to Better Evaluate NFL Players: A Review, MIT Sloan Sports Analytics Conference, 2022. paper
  • (basketball) Jeganathan: Stephanos et al., Machine learning predictive analytics for player movement prediction in NBA: applications, opportunities, and challenges, ACM Southeast Conference 2-8, 2021. doi
  • (basketball) Thor: Sarlis and Tjortjis, Sports analytics - Evaluation of basketball players and team performance, Information Systems 93:101562, 2020. doi
  • (cricket) Karthik: Kapadia et al., Sport analytics for cricket game results using machine learning: An experimental study, Applied Computing and Informatics 18:256-266. doi
  • (cricket) Md Bokhtiar, Minhas Wickramasinghe, Applications of Machine Learning in cricket: A systematic review, Machine Learning with Applications 10:100435, 2022. doi
  • (e-sports) Amir: Xenopoulos et al., Valuing Player Actions in Counter-Strike: Global Offensive, 2020 IEEE International Conference on Big Data 1283-1292, 2020. doi
  • (ice hockey) Jacob: Gu et al., A game-predicting expert system using big data and machine learning, Expert Systems with Applications, 130:293-305, 2019. doi
  • (ice hockey) Ludwig, Matteus: Moreau et al., Valuation of NHL draft picks using functional data analysis, Journal of Sports Analytics 11, 2025. doi
  • (football) Abbas: Manish et al., Prediction of Football Players Performance using Machine Learning and Deep Learning Algorithms, 2nd International Conference for Emerging Technology, 2021. doi
  • (football) Abuzar: Lolli et al., Data analytics in the football industry: a survey investigating operational frameworks and practices in professional clubs and national federations from around the world, Science and Medicine in Football 9:189-198, 2025. doi
  • (football) Alexander: Stafylidis et al., Key Performance Indicators Predictive of Success in Soccer: A Comprehensive Analysis of the Greek Soccer League, Journal of Functional Morphology and Kinesiology 9:107, 2024. doi
  • (football) Haoran, Zekai: Hewitt and Karakus, A machine learning approach for player and position adjusted expected goals in football (soccer), Franklin Open 4:100034, 2023. doi
  • (football) Kairui: Evers et al., Visual analytics of soccer player performance using objective ratings, Information Visualization 23:142-156, 2024. doi
  • (football) Mehmet: Cefis and Carpita, A new xG model for football analytics, Journal of the Operational Research Society 76:1-13, 2025. doi
  • (football) Ramon, Sabrina: Barthelemy et al., Impact of Technical-Tactical and Physical Performance on the Match Outcome in Professional Soccer: A Case Study, Journal of Human Kinetics 94:203-214, 2024. doi
    and
    Ruiz-de-Alarcon-Quintero and De-la-Cruz-Torres. An Expected Goals on Target (xGOT) Metric as a New Metric for Analyzing Elite Soccer Player Performance, Data 9:102, 2024. doi