MLSA 2015
Machine Learning and Data Mining for Sports Analytics

Table of Contents

• Preface
  
  
• Predictive Efficacy of a New Association Football League Format in Polish Ekstraklasa 1 - 9
  Jan Lasek , Marek Gagolewski
  
• Graph-based Approaches for Analyzing Team Interaction on the Example of Soccer 10 - 17
  Markus Brandt , Ulf Brefeld
  
• Valuation of Climbing Activities Using Multi-Scale Stochastic Neighbour Embedding 18 - 27
  Romain Herault , Jérémie Boulanger , Ludovic Seifert , John Aldo Lee
  
• Identifying Avatar Aliases in StarCraft 2 28 - 35
  Olivier Cavadenti , Victor Codocedo , Mehdi Kaytoue , Jean-François Boulicaut
  
• What Can Hawk-Eye Data Reveal about Serve Performance in Tennis? 36 - 45
  François Rioult , Sami Mecheri , Bruno Mantel , François Kauffmann , Nicolas Benguigui
  
• Network-based Measures for Predicting the Outcomes of Football Games 46 - 54
  Paolo Cintia , Salvatore Rinzivillo , Luca Pappalardo
  
• Learning Stochastic Models for Basketball Substitutions from Play-by-Play Data 55 - 64
  Harish S. Bhat , Li-Hsuan Huang , Sebastian Rodriguez
  
• Exploring Chance in NCAA Basketball 65 - 76
  Albrecht Zimmermann
  
• What is the Value of an Action in Ice Hockey? Q-Learning for the NHL 77 - 86
  Oliver Schulte , Zeyu Zhao , Kurt Routley
  
• Football Player's Performance and Market Value 87 - 95
  Miao He , Ricardo Cachucho , Arno Knobbe
  
• Estimating the Maximal Speed of Soccer Players on Scale 96 - 103
  Laszlo Gyarmati , Mohamed Hefeeda