Developing a Text Mining Framework to Analyze Cricket Match Commentary to Select Best Players

Abstract

Both the unpredictable nature of the game and the wide range of performance among players pose difficulties in selecting a cricket squad. When selecting players, it is important to consider their previous track record on the field. However, comparing performance indicators from previous games with those that are about to take place is far from a realistic approach. It was human opinion-live commentary (i.e., expert opinion)-that enabled us to make this a reality. Commentary is the best source of actual thoughts from veteran players at the time of any event because it is provided in real time. As a result, any knowledge gained from the commentary is beneficial to any player's overall performance metric. During our research, we established a framework for collecting actual commentary and analyzing it to determine performance indicators. For demonstrating the successful proposals from our framework, we have conducted many variants of testing. In our trial review, we discovered that our system could collect commentary and recommend the most likely best players for any forthcoming match with high efficiency.

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“…A real-time approach for analyzing cricket comments is presented by Roy et al [14], extracted performance indicators, and suggested the best players for forthcoming matches. A comprehensive evaluation confirms the effectiveness of the structure, propelling cricket analytics forward and developing a dependable method for commentary-based real-time player assessment.…”

“…Studies [12][13][14][15][16] focused on extracting information from commentary data for multiple purposes, including detecting key events [12], evaluating player performance [13,14], exploring cricket analytics [15], and extracting strength and weakness rules [11,16].…”