Data Mining the Harness Track and Predicting Outcomes

Data Mining the Harness Track and Predicting Outcomes

This paper presented the S&C Racing system that uses Support Vector Regression (SVR) to predict harness race finishes and analyzed it on fifteen months of data from Northfield Park. We found that our system outperforms the most common betting strategies of wagering on the favorites and the mathe...

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Veröffentlicht in:Journal of international technology and information management 2013-02, Vol.22 (2), p.103-108
1. Verfasser: Schumaker, Robert P
Format: Artikel
Sprache:eng
Schlagworte:
Accuracy
Algorithms
Arbitrage
Awards & honors
Data mining
Decision making
Engineering research
Gambling
Horse racing
Information systems
Machine learning
Methods
Prediction markets
Predictions
Racing
Regression analysis
Sports betting
Studies
Subject specialists
Support vector machines
Technology application
Variables
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Beschreibung
Zusammenfassung:This paper presented the S&C Racing system that uses Support Vector Regression (SVR) to predict harness race finishes and analyzed it on fifteen months of data from Northfield Park. We found that our system outperforms the most common betting strategies of wagering on the favorites and the mathematical arbitrage Dr. Z system in five of the seven wager types tested. This work would suggest that an informational inequality exists within the harness racing market that is not apparent to domain experts.
ISSN:1941-6679
1543-5962
1941-6679
DOI:10.58729/1941-6679.1330