Assessing the Performances of Soccer Players
暂无分享,去创建一个
[1] Ulf Brefeld,et al. Probabilistic movement models and zones of control , 2018, Machine Learning.
[2] Jesse Davis,et al. Automatically Discovering Offensive Patterns in Soccer Match Data , 2015, IDA.
[3] Jesse Davis,et al. Actions Speak Louder than Goals: Valuing Player Actions in Soccer , 2018, KDD.
[4] Lotte Bransen,et al. Measuring soccer players’ contributions to chance creation by valuing their passes , 2019, Journal of Quantitative Analysis in Sports.
[5] Jesse Davis,et al. Choke or Shine? Quantifying Soccer Players' Abilities to Perform Under Mental Pressure , 2019 .
[6] Konstantinos Pelechrinis,et al. The Anatomy of American Football: Evidence from 7 Years of NFL Game Data , 2016, PloS one.
[7] Sridha Sridharan,et al. Forecasting the Next Shot Location in Tennis Using Fine-Grained Spatiotemporal Tracking Data , 2016, IEEE Transactions on Knowledge and Data Engineering.
[8] Jürgen Perl,et al. Evaluation of changes in space control due to passing behavior in elite soccer using Voronoi-cells , 2016 .
[9] Padraig Cunningham,et al. Marathon Race Planning: A Case-Based Reasoning Approach , 2018, IJCAI.
[10] Dino Pedreschi,et al. PlayeRank: Multi-dimensional and role-aware rating of soccer player performance , 2018, ArXiv.
[11] Goldner Keith,et al. A Markov Model of Football: Using Stochastic Processes to Model a Football Drive , 2012 .
[12] Ryan P. Adams,et al. Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball , 2014, ICML.
[13] Jesse Davis,et al. Automatic Discovery of Tactics in Spatio-Temporal Soccer Match Data , 2018, KDD.
[14] Luke Bornn,et al. Adjusting for scorekeeper bias in NBA box scores , 2017, Data Mining and Knowledge Discovery.
[15] Arno J. Knobbe,et al. Sports analytics for professional speed skating , 2017, Data Mining and Knowledge Discovery.
[16] Filip De Turck,et al. Enabling training personalization by predicting the session rate of perceived exertion (sRPE) , 2017, PKDD 2017.
[17] Wannes Meert,et al. Fatigue Prediction in Outdoor Runners Via Machine Learning and Sensor Fusion , 2018, KDD.
[18] Peter Carr,et al. Assessing team strategy using spatiotemporal data , 2013, KDD.
[19] Jesse Davis,et al. Who Will Win It? An In-game Win Probability Model for Football , 2019, ArXiv.
[20] Tim Op De Beéck,et al. Predicting Future Perceived Wellness in Professional Soccer: The Role of Preceding Load and Wellness. , 2019, International journal of sports physiology and performance.
[21] Jesse Davis,et al. Predicting Soccer Highlights from Spatio-Temporal Match Event Streams , 2017, AAAI.
[22] Kirk Goldsberry,et al. POINTWISE: Predicting Points and Valuing Decisions in Real Time with NBA Optical Tracking Data , 2014 .
[23] Jesse Davis,et al. STARSS: A Spatio-Temporal Action Rating System for Soccer , 2017, MLSA@PKDD/ECML.
[24] Oliver Schulte,et al. Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluation , 2018, IJCAI.
[25] Filip Staes,et al. Title : Relationships Between the External and Internal Training Load in Professional Soccer : What Can We Learn From Machine Learning ? , 2017 .
[26] Jesse Davis,et al. Strategy discovery in professional soccer match data , 2016, KDD 2016.
[27] Daniel Link,et al. Real Time Quantification of Dangerousity in Football Using Spatiotemporal Tracking Data , 2016, PloS one.
[28] Pascal Fua,et al. Analyzing Volleyball Match Data from the 2014 World Championships Using Machine Learning Techniques , 2016, KDD.
[29] Iain Matthews,et al. "Quality vs Quantity": Improved Shot Prediction in Soccer using Strategic Features from Spatiotemporal Data , 2015 .