Duckworth–Lewis–Stern modeling with fuzzy logic and contextual indices for target revision in cricket

In limited-overs cricket, rain interruptions require adjustment of the target score for the chasing team. The Duckworth-Lewis-Stern (DLS) method is widely used for this purpose but does not explicitly include factors such as pitch condition, dew accumulation, or player strength. To address this limitation, we propose a Fuzzy-DLS model that includes fuzzy logic into a generalized resource function. The method allows batting quality index (BQI), bowling threat index (BTI), pitch state, and weather effects to adjust the resource curve in a continuous and interpretable way. For the 30 illustrative cases in Appendix A, the proposed formulation differs from the DLS resources by a mean absolute amount of 0.0152, with a mean relative difference of [Formula: see text] and a mean absolute par-score difference of 2.13 runs. In the 100-match ODI sample analysed here, chasing teams won [Formula: see text] of winter matches compared with [Formula: see text] in non-winter matches, giving an odds ratio of 2.21 and a chi-square p-value of 0.081. These results support the use of fuzzy match-condition inputs transparently.