Detection of bowler's strong and weak area in cricket through commentary

Arif, Subhan; Umair, Muhammad; Naqvi, Syed Muhammad Kumail; Ikram, Ahmad; Ikram, Anam

doi:10.1145/3231053.3234322

Cited by 5 publications

(6 citation statements)

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“…To improve the identification of significant events and offer more complex insights into athletic narratives, this study investigated sentiment analysis. Association rule mining was used by Arif et al [13] to extract features, such as bowling position, location, and wickets per inning. Using statistical techniques to examine post-text extraction, this study seeks to provide meaningful data.…”

Section: Structuring Unstructured Text Commentarymentioning

confidence: 99%

“…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].…”

Section: Introductionmentioning

confidence: 99%

“…In-Depth Sport-Specific Attributes: Many existing studies depend on aggregate data [12,13,17,28], yet a strategic plan demands more nuanced and in-depth information. This plan requires the incorporation of the actual execution of sports activities, encompassing the essential sport-specific attributes inherent in these activities.…”

Section: Introductionmentioning

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: Structuring Unstructured Text Commentarymentioning

confidence: 99%

Section: Introductionmentioning

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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“…They used biplots to plot a relationship between bowler and batsman using the dimensionality reduction technique. Arif et al [9] used text commentary to identify the strengths and weaknesses of cricket bowlers. An a priori algorithm is applied to a player's data by taking into account factors such as the home venue or away playing conditions.…”

Section: Analysis Using Commentary Corpusmentioning

confidence: 99%

Impact Calculation Of The Players Using The Cricket Commentary Corpus

Goel

Singh

2023

Preprint

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This research paper focuses on the use of natural language processing techniques for extracting insights from cricket commentary. This study proposes a framework that considers the commentary text, evaluates each player's performance, and gives value-based scores to define their impacts. This research relies on sentiment analysis, topic modeling, and NER to analyze a large corpus of cricket commentary data and develop a model for calculating the impacts of the players. The findings of this study will be of great interest to sports analysts, coaches, players, and fans of the game. The literature review of this paper covers the existing works on textual analysis and analysis using commentary corpora. This study has the potential to revolutionize player performance evaluation in cricket by identifying "hidden gems" that may have been overlooked based on conventional statistics alone.

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“…Arif et al [2] have proposed a bowler's gaming prowess can be determined from related commentary. Bowler's strengths and limitations that can be determined from textual data are also applicable when deciding his chance in the team for upcoming matches.…”

Section: Related Workmentioning

confidence: 99%

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

Roy

Rahman

Kaiser

et al. 2021

Lecture Notes on Data Engineering and Communications Technologies

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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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Detection of bowler's strong and weak area in cricket through commentary

Cited by 5 publications

References 5 publications

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

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

Impact Calculation Of The Players Using The Cricket Commentary Corpus

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

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