Player-aware resource compensation in interrupted cricket matches

Salam Zia; Hannan Bin Liaqat; Hafiz Usman Zia; Xiangjie Kong; Sultan Shamshad

doi:10.7717/peerj-cs.917

Player-aware resource compensation in interrupted cricket matches

PeerJ Comput Sci. 2022 Mar 14:8:e917. doi: 10.7717/peerj-cs.917. eCollection 2022.

Authors

Salam Zia¹, Hannan Bin Liaqat¹, Hafiz Usman Zia¹, Xiangjie Kong², Sultan Shamshad¹

Affiliations

¹ Department of Information Technology, University of Gujrat, Gujrat, Pakistan.
² College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China.

Abstract

The International Cricket Council (ICC) uses the Duckworth-Lewis-Stern (DLS) method for resource compensation in interrupted games, which is an upgraded version of the Duckworth-Lewis (D/L) method. In order to compensate resources, the D/L method uses a generic resource table for all teams without considering both teams' past performance, venue of the match, and players participating in that match. That is why teams cannot strategize according to their strengths and play according to D/L's requirements. This paper presents a method for Player-aware Resource Compensation in Interrupted Cricket Matches (PRCICM). The PRCICM model is dynamic because it allocates a different number of resources to different teams based on their resource usage in the past, players involved in the match and venue of the match. The proposed method eliminates the need to find the generalized scoring patterns with a player-driven approach. A team-specific approach is more appropriate because of teams' different formations and playing approaches.

Keywords: Cricket; OR in sports; Regression; Resource compensation; Sports.

Grants and funding

This work is supported by the National Natural Science Foundation of China (No. 62072409), the Zhejiang Provincial Natural Science Foundation (No. LR21F020003), and the Fundamental Research Funds for the Provincial Universities of Zhejiang (No. RF-B2020001). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.