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Publications related to Sports Analytics research at LiU



  • Lehmus Persson T, Kozlica H, Carlsson N, Lambrix P, Prediction of tiers in the ranking of ice hockey players, 7th Workshop on Machine Learning and Data Mining for Sports Analytics, CCIS 1324, 89-100, Gent, Belgium, 2020. doi, pdf, extended version of paper, video
  • Lindström P, Jacobsson L, Carlsson N, Lambrix P, Predicting Player Trajectories in Shot Situations in Soccer, 7th Workshop on Machine Learning and Data Mining for Sports Analytics, CCIS 1324, 62-75, Gent, Belgium, 2020. (Presented at MLSA 2019 in Würzburg, Germany, 2019. Due to problem related to MLSA 2019 proceedings generation published in MLSA 2020 proceedings.) doi, slides


  • Robin Keskisärkkä, Huanyu Li, Sijin Cheng, Niklas Carlsson, Patrick Lambrix, An Ontology for Ice Hockey, ISWC 2019 Satellites - Proceedings of the ISWC 2019 Satellite Tracks (Posters & Demonstrations, Industry, and Outrageous Ideas) co-located with 18th International Semantic Web Conference (ISWC 2019), CEUR Workshop Proceedings Volume 2456, 13-16, Auckland, New Zealand, 2019. pdf
  • Carles Sans Fuentes, Niklas Carlsson, Patrick Lambrix, Player impact measures for scoring in ice hockey, MathSport International 2019 Conference, 307-317, Athens, Greece, 2019. pdf, slides


  • Daniel de Leng, Mattias Tiger, Mathias Almquist, Viktor Almquist, Niklas Carlsson, "A Second Screen Journey to the Cup: Twitter Dynamics during the Stanley Cup Playoffs", Proc. IEEE/IFIP Network Traffic Measurement and Analysis Conference (TMA), Vienna, Austria, June 2018. doi, pdf, slides
  • Dennis Ljung, Niklas Carlsson, Patrick Lambrix, Player pairs valuation in ice hockey, Machine Learning and Data Mining for Sports Analytics. MLSA 2018, Dublin, Ireland, LNAI 11330, 82-92, 2019. (workshop 2018, final publication 2019) doi, pdf
  • Edward Nsolo, Patrick Lambrix, Niklas Carlsson, Player valuation in European football, Machine Learning and Data Mining for Sports Analytics. MLSA 2018, Dublin, Ireland, LNAI 11330, 42-54, 2019. (workshop 2018, final publication 2019) doi, pdf, pdf-extended version, slides


  • Marcus Bendtsen, Regimes in baseball players' career data, Data Mining and Knowledge Discovery 31(6):1580-1621, 2017. doi

Master and Bachelor theses

  • Rynell R, Persson J, Ett scoutingverktyg åt Linköping Hockey Club, LIU-IDA/LITH-EX-G--21/058--SE, 2021.
  • Stjernberg F, Tell J, Scout Enhancer - En applikation som visualiserar spelardata för att förbättra scouting processer, LIU-IDA/LITH-EX-G--21/051--SE, 2021.
  • Carsting T, Gummesson J, GoalMate - An Application for Visualization of Ice Hockey Statistics, LIU-IDA/LITH-EX-G--21/049--SE, 2021.
  • Ljung D, Using Reinforcement Learning to Evaluate Player Pair Performance in Ice Hockey, LIU-IDA/LITH-EX-A--21/014--SE, 2021.
  • Vik J, Not All Goals Are Created Equal - Evaluating Hockey Players in the NHL Using Q-Learning with a Contextual Reward Function, LIU-IDA/LITH-EX-A--21/008--SE, 2021.
  • Kozlica H, Lehmus Persson T, Prediktion av NHL-spelares ranking - En jämförelse mellan olika metoder för klassificering och variabelselektion, 2020.
  • Lindström P, Deep Imitation Learning on Spatio-Temporal Data with Multiple Adversarial Agents Applied on Soccer. LIU-IDA/LITH-EX-A--19/036--SE, 2019.
  • Sans Fuentes C, Markov Decision Processes and ARIMA models to analyze and predict Ice Hockey player's performance. LIU-IDA/STAT-A--19/001--SE, 2019.
  • Gonzalez Dos Santos T, NBA Game Prediction and Season Simulation - Statistics Applied to Sport. LIU-IDA/STAT-A--19/005--SE, 2019.
  • Nsolo E, Prediction models for soccer sports analytics. LIU-IDA/LITH-EX-A--18/021--SE, 2018.
  • Alvarsson A, The development of a sports statistics web application. LIU-IDA/LITH-EX-A--17/030--SE, 2017.

Page responsible: Patrick Lambrix
Last updated: 2021-10-27