~ Nonlinear Adaptive Filtering as a Form of Artificial Intelligence ~
 Home History References Contact

Only data, no code

## Bookmakers' bias in sports betting

The authors assume that the readers are familiar with basic terms in sports betting. If not, please use online help to learn, it may take only a few minutes.

### Can bias be corrected?

No. Bookmakers can make similar or even more accurate models, but the public will bring chaos and enforce adjustment.

### Conclusion

Using bookmakers' bets for predicting of outcomes is not a new idea. This opportunity was noticed by many other authors, for example:

Odachowski K., Grekow J. (2013) Using Bookmaker Odds to Predict the Final Result of Football Matches. In: Graña M., Toro C., Howlett R.J., Jain L.C. (eds) Knowledge Engineering, Machine Learning and Lattice Computing with Applications. KES 2012. Lecture Notes in Computer Science, vol 7828. Springer, Berlin, Heidelberg.

Online copy is available.

The approach in published paper is different. Authors tracked changes in bets for the short period before the match and trained AI to predict outcomes based on changes in bets and not by final values. However, it showed the same tendency of bias in bookmakers' bets forced by balancing expected commissions by making certain bets more and others less attractive.