Using SVM Regression to Predict Harness Races: A One Year Study of Northfield Park
نویسنده
چکیده
Can data mining tools be successfully applied to wagering-centric events like harness racing? We demonstrate the S&C Racing system that uses Support Vector Regression (SVR) to predict harness race finishes and tested it on one year of data from Northfield Park, evaluating accuracy, payout and betting efficiency. Depending upon the level of wagering risk taken, our system could make either high accuracy/low payout or low accuracy/high payout wagers. To put this in perspective, when set to risk averse, S&C Racing managed a 92% accuracy with a $110.90 payout over an entire year. Conversely, to maximize payout, S&C Racing Win accuracy dropped to 57.5% with a $1,437.20 return. While interesting, the implications of S&C Racing in this domain shows promise.
منابع مشابه
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