Optimal playing strategies of a batsman against bowling type in limited-over cricket: An application of game theory

Das, Dhruba; Saikia, Hemanta; Bhattacharjee, Dibyojyoti

doi:10.1080/23737484.2022.2133027

Cited by 1 publication

(3 citation statements)

References 7 publications

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“…Game theory is used by Das et al [24] to investigate the best batting tactics in cricket against various bowling styles. In light of the batsman's critical role in shaping the posture of the field team, this study attempts to reveal practical batting strategies for different types of bowlers through real-time data analysis.…”

Section: Context-aware Strategiesmentioning

confidence: 99%

“…Furthermore, studies have explored the utilization of big data for cricket match outcome prediction [9], sports analytics for cricket games [21], offering a unique approach to ranking cricket teams [23], and conducting a comparative analysis of pitch ratings for all formats of cricket [22]. Finally, studies [24][25][26][27], collectively explored strategic decision-making and performance evaluation in cricket, covering optimal playing strategies against specific bowling types using game theory [24], player-aware resource compensation in interrupted matches [25], investigating the influence of the T20 cricket on Test cricket performance and team quality [26], and estimating a batsman's shot selection in T20 cricket to guide strategic decisions related to fielder placement [27].…”

Section: Introductionmentioning

confidence: 99%

“…Context-Aware Strategies: A gap exists in the understanding and implementation of context-aware strategies in cricket analytics. Current approaches [24][25][26][27] do not adequately consider contextual factors such as powerplays, the number of fielders in the circle and outer circle, and specific line and length variations.…”

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confidence: 99%

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RunsGuard Framework: Context Aware Cricket Game Strategy for Field Placement and Score Containment

Hussain,

Arshad,

Hassan

2024

Applied Sciences

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Sports analytics utilizes data analysis techniques and computational methods to gain insights, make informed decisions, and facilitate improvements in the performance of individuals and teams. Cricket is one of the most popular games and continues to evolve worldwide. The availability of ball-by-ball data demands in-depth investigation of player strategies, team dynamics, and the impact of contextual variables. Existing studies explored various aspects of cricket analytics, including detecting key events, predicting outcomes, and ranking teams. However, the literature lacks a comprehensive integrated framework that processes unstructured sports commentary, extracts actionable insights, conducts a thorough player analysis, and develops strategic plans while considering contextual factors. This work aims to propose a bowling and fielding strategy to contain a batsman. For this purpose, we developed a comprehensive context-aware framework that collects data, extracts insights from commentary, identifies player strengths and weaknesses, and proposes cricket bowling and fielding strategies according to the given context. To evaluate this work, we implemented a case study that simulated different scenarios, and our framework suggested bowling and fielding strategies. In these simulations, the proposed strategies consistently demonstrated a substantial reduction in the number of runs that were scored. On average, the framework reduces the batsman’s score rate by 33%. These findings underscore the practical effectiveness of research in optimizing field placement and effectively reducing scoring opportunities. Finally, by bridging the gap between data analytics and cricket game strategy, this methodology provides a competitive advantage to coaches, captains, and players. In the future, we aim to involve temporal patterns to understand the evolving behavior of players.

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Section: Context-aware Strategiesmentioning

confidence: 99%