Duckworth-Lewis-Stern Method Comparison with Machine Learning Approach
This work addresses match prediction and team ranking in cricket, but it is incremental as it builds on existing methods like DLS.
This paper tackled the problem of predicting One Day International cricket match outcomes by comparing the Duckworth-Lewis-Stern method with machine learning algorithms and optimizing its resource table, resulting in improved predictive accuracy and the development of an Unpredictability Index for ranking teams.
This work presents an analysis of the Duckworth-Lewis-Stern (DLS) method for One Day International (ODI) cricket matches. The accuracy of the DLS method is compared against various supervised learning algorithms for result prediction. The result of a cricket match is predicted during the second inning. The paper also optimized DLS resource table which is used in the Duckworth-Lewis (D/L) formula to increase its predictive power. Finally, an Unpredictability Index is developed that ranks different cricket playing nations according to how unpredictable they are while playing an ODI match.