교차 검증의 다이어그램
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4. Conclusions
One of the vital applications in sport that requires good predictive accuracy is match result prediction. Traditionally, the results of the matches are predicted using mathematical and statistical models that are often verified by a domain expert. Due to the specific nature of match-related features to different sports, results across different studies in this application can generally not be compared directly. Despite the increasing use of ML models for sport prediction, more accurate models are needed. This is due to the high volumes of betting on sport, and for sport managers seeking useful knowledge for modelling future matching strategies. Therefore, ML seems an appropriate methodology for sport prediction since it generates predictive models that can predict match results using predefined features in a historical dataset.
This article critically analyses some recent research on sport prediction that have used ANN, and following this, we proposed a sport result prediction ‘SRP-CRISP-DM’ framework for the complex problem of sport result prediction. Moreover, challenges facing the sport prediction application were shown to pinpoint future work for scholars in this important application. Future studies concerning ML in sport result prediction research will hopefully be benefitted by this study.