2024

• Sävfenberg R, Carlsson N, Lambrix P, Identifying Player Roles in Ice Hockey, 10th Workshop on Machine Learning and Data Mining for Sports Analytics - MLSA 2023, CCIS 2035, 131-143 Torino, Italy, 2024. preprint, video, slides

2023

• Brecht T, Carlsson N, Vernblom M, Lambrix P, Proceedings of the Linköping Hockey Analytics Conference LINHAC 2023 Research Track, LECP 201, Linköping, Sweden, 2023. doi
• Sävfenberg R, Carlsson N, Lambrix P, Simple and Practical Goal Importance Metrics, Linköping Hockey Analytics Conference, LECP 201, 40-52, Linköping, Sweden, 2023. doi, video
• Sävfenberg R, Svarén M, Carlsson N, Lambrix P, The Importance of Special Teams in Ice Hockey, Linköping Hockey Analytics Conference, LECP 201, 53-65, Linköping, Sweden, 2023. doi, video

2022

• Gonzalez Dos Santos T, Wang C, Carlsson N, Lambrix P, Predicting Season Outcomes for the NBA, 8th Workshop on Machine Learning and Data Mining for Sports Analytics (2021), CCIS 1517, 129-142, Virtual Conference, 2022. doi, pdf, extended version of paper, slides, video
• Lambrix P, Carlsson N, Performance Metrics for Ice Hockey Accounting for Goal Importance, Linköping Hockey Analytics Conference, LECP 191, 11-25, Linköping, Sweden 2022. doi
• Lambrix P, Carlsson N, Vernblom M, (eds), Proceedings of the Linköping Hockey Analytics Conference LINHAC 2022 Research Track, LECP 191, Linköping, Sweden, 2022. doi

2021

• Vik J, Shih M-C, Jansher, R, Carlsson N, Lambrix P, Not all goals are equally important - a study for the NHL, MathSport International 2021 Conference, 26-31, Virtual, 2021. pdf, extended version of paper, slides, video (talk starts at 1:20:19)

2020

• 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

2019

• 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

2018

• 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

2017

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

• Broman S, Forsberg L, Automatic Sport Analysis System for Table-Tennis using Image Recognition Method, LIU-IDA/LITH-EX-A--23/084--SE, 2023.
• Samuelsson N, Shooting for Perfection - Leveraging Basketball Movement Data to Predict Shot Accuracy, LIU-IDA/LITH-EX-A--23/079--SE, 2023.
• Usman Y, Context Matters for Evaluating the Performance of Ice Hockey Players, LIU-IDA/LITH-EX-A--22/104--SE, 2022.
• Baby D, Shi M, NHL Game Prediction and Season Simulation, LIU-IDA/LITH-EX-A--22/099--SE, 2022.
• 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.