<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Realizing the significant effect that misprediction has on many real-world problems, our paper is focused on the way these costs could affect the sports sector in terms of soccer outcome predictions. In our experimental analysis, we consider the potential influence of a cost-sensitive approach rather than traditional machine-learning methods. Although the measurement of prediction accuracy is a very important part of the validation of each model, we also study its economic significance. As a performance metric for our models, the Sharpe ratio metric is calculated and analyzed. Seeking to improve Sharpe ratio value, a genetic algorithm is applied. The empirical study and evaluation procedure of the paper are primarily based on English Premier League’s games, simple historical data and well-known bookmakers’ markets odds. Our research confirms that it is worthwhile to employ cost-sensitive methods for the successful predictions of soccer results and better investment opportunities.</p></abstract>

Realizing the significant effect that misprediction has on many real-world problems, our paper is focused on the way these costs could affect the sports sector in terms of soccer outcome predictions. In our experimental analysis, we consider the potential influence of a cost-sensitive approach rather than traditional machine-learning methods. Although the measurement of prediction accuracy is a very important part of the validation of each model, we also study its economic significance. As a performance metric for our models, the Sharpe ratio metric is calculated and analyzed. Seeking to improve Sharpe ratio value, a genetic algorithm is applied. The empirical study and evaluation procedure of the paper are primarily based on English Premier League’s games, simple historical data and well-known bookmakers’ markets odds. Our research confirms that it is worthwhile to employ cost-sensitive methods for the successful predictions of soccer results and better investment opportunities.

Forecasting Soccer Outcome Using Cost-Sensitive Models Oriented to Investment Opportunities

International Journal of Computer Science in Sport

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Realizing the significant effect that misprediction has on many real-world problems, our paper is focused on the way these costs could affect the sports sector...

Forecasting Soccer Outcome Using Cost-Sensitive Models Oriented to Investment Opportunities

Online veröffentlicht: 21. Aug. 2019

Seitenbereich: 93 - 114

DOI: https://doi.org/10.2478/ijcss-2019-0006

Schlüsselwörter
soccer forecasting, cost-sensitive classification, binary data set, genetic algorithm, prediction models

© 2019 K. Talattinis et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Forecasting Soccer Outcome Using Cost-Sensitive Models Oriented to Investment Opportunities

Online veröffentlicht: 21. Aug. 2019

Seitenbereich: 93 - 114

DOI: https://doi.org/10.2478/ijcss-2019-0006

Schlüsselwörtersoccer forecasting, cost-sensitive classification, binary data set, genetic algorithm, prediction models

© 2019 K. Talattinis et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
soccer forecasting, cost-sensitive classification, binary data set, genetic algorithm, prediction models