Learning Betting Tips from Users’ Bet Selections

  • Erik Štrumbelj
  • Marko Robnik Šikonja
  • Igor Kononenko
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5632)

Abstract

In this paper we address the problem of using bet selections of a large number of mostly non-expert users to improve sports betting tips. A similarity based approach is used to describe individual users’ strategies and we propose two different scoring functions to evaluate them. The information contained in users’ bet selections improves on using only bookmaker odds. Even when only bookmaker odds are used, the approach gives results comparable to those of a regression-based forecasting model.

Keywords

Machine learning data mining nearest neighbors forecasting sports betting 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Erik Štrumbelj
    • 1
  • Marko Robnik Šikonja
    • 1
  • Igor Kononenko
    • 1
  1. 1.Faculty of Computer and Information ScienceUniversity of LjubljanaLjubljanaSlovenia

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