Assessing the Performances of Soccer Players

A key question within sports analytics is how to analyze match data in order to objectively assess a player’s performance during a match. This paper summarizes our recent attempts to address this question for soccer. First, we look at how to assign a value to each on-the-ball action a soccer player performs during a match. Second, we explore how these values depend on the level of mental pressure that the player experienced when performing the action. We conclude by briefly highlighting some potential applications of this work.

[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 .