On estimating shot selection by a batsman in Twenty20 cricket: A probabilistic approach

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

“…Weaknesses include the emphasis on Test cricket, the recommendation for more study on the impact of T20 matches in one-day internationals, and the strategic consideration of variables such as home-field advantage and team caliber. In six different cricket field settings, Das et al [27] evaluated a batsman's stroke selection against a variety of bowling styles using a probabilistic model. For shot probability, the research used a multinomial distribution; for transition probabilities and mean recurrence time, it used Markov chain analysis.…”

“…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].…”

“…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.…”