Cricket, "a Gentleman's Game", is a prominent sport rising worldwide. Due to the rising competitiveness of the sport, players and team management have become more professional with their approach. Prior studies predicted individual performance or chose the best team but did not highlight the batter's potential. On the other hand, our research aims to evaluate a player's impact while considering his control in various circumstances. This paper seeks to understand the conundrum behind this impactful performance by determining how much control a player has over the circumstances and generating the "Effective Runs",a new measure we propose. We first gathered the fundamental cricket data from open-source datasets; however, variables like pitch, weather, and control were not readily available for all matches. As a result, we compiled our corpus data by analyzing the commentary of the match summaries. This gave us an insight into the particular game's weather and pitch conditions. Furthermore, ball-by-ball inspection from the commentary led us to determine the control of the shots played by the batter. We collected data for the entire One Day International career, up to February 2022, of 3 prominent cricket players: Rohit G Sharma, David A Warner, and Kane S Williamson. Lastly, to prepare the dataset, we encoded, scaled, and split the dataset to train and test Machine Learning Algorithms. We used Multiple Linear Regression (MLR), Polynomial Regression, Support Vector Regression (SVR), Decision Tree Regression, and Random Forest Regression on each player's data individually to train them and predict the Impact the player will have on the game. Multiple Linear Regression and Random Forest give the best predictions accuracy of 90.16 percent and 87.12 percent, respectively.

翻译：Cricket,“Gentleman's Gentleman' Game”,是全世界最突出的体育。由于体育、球员和球队管理越来越具有专业性,因此他们的做法越来越专业。先前的研究预测了个人的表现或选择了最好的球队,但没有突出击球者的潜力。另一方面,我们的研究旨在评估球员的影响,同时考虑他在不同情况下的控制。本文试图通过确定球员对情况的控制程度和产生“有效运行”来理解这一影响性表现背后的难题。由于体育、球员和球队管理越来越具有更高的竞争力。我们首先从开放源数据集中收集了基本的板球员数据;然而,球员、球员和球队管理者、球员管理者、球员管理者、球员管理者、球员管理者、球迷、球员管理者、球迷、球迷、球迷、球迷、球迷、球迷、球迷、球迷、球迷、球迷、球迷、球迷、球迷、球迷、球迷、球迷、球迷、球迷、球迷、球迷数据。