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Accurately predicting the outcome of sporting events has been a goal for manygroups who seek to maximize profit. What makes this challenging is that theoutcome of an event can be influenced by many factors that dynamically changeacross time. Oddsmakers attempt to estimate these factors by using bothalgorithmic and subjective methods to set the spread. However, it is well-knownthat both human and algorithmic decision-making can be biased, so this paperexplores if oddsmaker biases can be used in an exploitative manner, in order toimprove the prediction of NFL game outcomes. Real-world gambling data was usedto train and test different predictive models under varying assumptions. Theresults show that methods that leverage oddsmaker biases in an exploitativemanner perform best under the conditions tested in this paper. These findingssuggest that leveraging human and algorithmic decision biases in anexploitative manner may be useful for predicting the outcomes of competitiveevents, and could lead to increased profit for those who have financialinterest in the outcomes.

Exploiting oddsmaker bias to improve the prediction of NFL outcomes