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753A01 Sports Analytics

Timetable


  • March 31, 2022, 13:15-15:00, Introduction (Patrick Lambrix)
  • April 1, 2022, 10:15-12:00, Ice Hockey Analytics research at IDA (Patrick Lambrix)
  • April 5, 2022, 10:15-12:00, Football and Basketball Analytics research at IDA (Patrick Lambrix)
  • April 26, 2022, 15:15-17:00, Baseball Analytics (Marcus Bendtsen)
  • April 27, 2022, 10:15-12:00, Football Analytics at Signality (Ludvig Jacobsson, Signality)
  • April 28, 2022, 13:15-15:00, Ice Hockey Analytics at LHC (Mikael Vernblom, LHC)
  • May 13, 2022, 10:15-12:00, student presentations football: Oscar M and David, Farid, Olof
  • May 20, 2022, 10:15-12:00, student presentations football: Oscar K, Syed; American football: Fahim
  • May 23, 2022, 15:15-17:00, student presentations cricket: Siddarth, Keshav
  • May 24, 2022, 10:15-12:00, student presentations e-sports: Shashi and Rojan; baseball: Mina
  • May 25, 2022, 10:15-12:00, student presentations basketball: Ying, Adesijibomi; volleyball: Rodrigo
  • August, 2022, student presentations: Tejashree, Sreenand, Adithiya, Ravinder
Student presentations
  • * (basketball) Ying: Nistala and Guttag, Using Deep Learning to Understand Patterns of Player Movement in the NBA, MIT Sloan Sports Analytics Conference, 2019. paper
  • ** (baseball) Mina: Martin, Predicting Major League Baseball Strikeout Rates from Differences in Velocity and Movement Among Player Pitch Type, MIT Sloan Sports Analytics Conference, 2019. paper
  • ** (American football) Fahim: Horton, Learning Feature Representations from Football Tracking, MIT Sloan Sports Analytics Conference, 2020. paper
  • ** (football) Oscar M and David: Constantinou, Dolores: a model that predicts football match outcomes from all over the world, Machine Learning 108:49-75, 2019. doi
    and Tsokos et al., Modeling outcomes of soccer matches, Machine Learning 108:77-95, 2019. doi
  • ** (e-sports) Shashi and Rojan: Clark et al., A Bayesian adjusted plus-minus analysis for the esport Dota 2, Journal of Quantitative Analysis in Sports 16:325-341, 2020. doi
    and Gourdeau and Archambault, Discriminative Neural Network for Hero Selection in Professional Heroes of the Storm and DOTA 2, IEEE Transactions on Games, 13:380-387, 2021. doi
  • ** (football) Farid: Decroos et al., Actions Speak Louder than Goals: Valuing Player Actions in Soccer, 25th ACM SIGKDD International Conference 1851-1861, 2019. doi
  • ** (football) Oscar K: Berrar et al., Incorporating domain knowledge in machine learning for soccer outcome prediction Machine Learning 108:97-126, 2019. doi
  • * (basketball) Adesijibomi: Deshpande and Jensen, Estimating an NBA player's impact on his team's chances of winning, Journal of Quantitative Analysis in Sports 12:51-72, 2016. doi
  • (cricket) Ravinder: Stevenson and Brewer, Finding your feet: A Gaussian process model for estimating the abilities of batsmen in test cricket, Journal of the Royal Statistical Society: Series C (Applied Statistics) 70:481-506, 2021. doi
  • ** (football) Olof: Bojinov and Bornn, The Pressing Game: Optimal Defensive Disruption in Soccer, MIT Sloan Sports Analytics Conference, 2016. paper
  • ** (football) Syed: Whitaker et al., Visualizing a Team's Goal Chances in Soccer from Attacking Events: A Bayesian Inference Approach, Big Data 6, 2018. doi
  • ** (cricket) Siddharth: Asif and McHale, In-play forecasting of win probability in One-Day International cricket: A dynamic logistic regression model, International Journal of Forecasting 32:34-43. doi
  • * (volleyball) Rodrigo: Drikos et al., Game variables that predict success and performance level in elite men's volleyball, International Journal of Performance Analysis in Sport 21:767-779, 2021. doi
  • ** (cricket) Keshav: Rama Iyer and Sharda, Prediction of athletes performance using neural networks: An application in cricket team selection, Expert Systems with Applications: An International Journal 36:5510-5522, 2009. doi
  • (football) Tejashree: Kampakis, Comparison of machine learning methods for predicting the recovery time of professional football players after an undiagnosed injury, Proceedings of the 1st Workshop on Machine Learning and Data Mining for Sports Analytics 58-68, 2013. paper


Page responsible: Patrick Lambrix
Last updated: 2022-05-24