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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: Sreenand, 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
  • (e-sports) Sreenand: Semenov et al., Performance of Machine Learning Algorithms in Predicting Game Outcome from Drafts in Dota 2, International Conference on Analysis of Images, Social Networks and Texts, 26-37, 2016. doi

Page responsible: Patrick Lambrix
Last updated: 2022-08-29