Sports Analytics, vt 2019

Introduction

Sports analytics deals with using data related to sports events to obtain insights about the sport and its surroundings. The insights can relate to such things as player and team performance, strategies, training, injuries, and rules of the game.

Goals

- To gain an understanding of the research issues related to sports analytics
- To obtain knowledge about problems in sports analytics and algorithms for solving these problems
- To be able to use relevant algorithms in a sports analytics application

Course plan

See the course plan at the PhD student portal.

Timetable

This time table will be updated when new info becomes available.

• February 22, 2019, 13:15- 16:00, von Neumann
  • Introduction (Patrick) Bring your calendars for booking the student presentation sessions.
  • Introduction to data mining and machine learning algorithms (refreshing knowledge from previous courses) (Isak)
• March 5, 10:15-12:00, Alan Turing: Sports Analytics research at IDA (Patrick)
• March 8, 2019, 13:15, von Neumann: Football Analytics at Signality (Ludvig Jacobsson, Signality)
• March 13, 2019, 13:15, von Neumann: Baseball Analytics (Marcus)
• April 24, 2019, 15:15, Ada Lovelace: Football Analytics (prof Jesse Davis, KU Leuven)
• April 29, 2019, 13:15-15:00, von Neumann: student presentations (Jon, Kristian, Pontus, Erik)
• May 6, 2019, 10:15-12:00, Alan Turing: student presentations (Teodor, Oulimede, Sijin, Stefano)
• May 10, 2019, 13:15-15:00, von Neumann: student presentations (Huanyu, Robin, Martin, Isak)
• May 22, 2019, 13:15-15:00, von Neumann: Ice hockey Analytics (Mikael Vernblom, LHC)

Page responsible: SA
Last updated: 2020-01-16