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The most profound technologies are those that disappear. They weave themselves into fabrics of everyday life until they are indistinguishable from it [1]. This research work is a mere effort for automated decision making during sports of…

Other Computer Science · Computer Science 2011-09-29 Wazir Zada Khan , Mohammed Y. Aalsalem , Quratul Ain Arshad

Player synergies are a salient feature of team sports. In the team game of cricket, player synergies may be reflected in batting partnerships. Batting partnerships have been analysed extensively. In this paper, we introduce and precisely…

Social and Information Networks · Computer Science 2021-08-31 Praharsh Nanavati , Amit Anil Nanavati

Player performance prediction is a serious problem in every sport since it brings valuable future information for managers to make important decisions. In baseball industries, there already existed variable prediction systems and many types…

Machine Learning · Computer Science 2022-06-22 Hsuan-Cheng Sun , Tse-Yu Lin , Yen-Lung Tsai

We propose a model for recalculating the target score in rain affected matches based on empirical data. During the development of the current stage of the Cricket, different methods have been introduced to recalculate the target scores in…

Other Statistics · Statistics 2018-04-09 Robin de Regt , Ravinder Kumar

Predicting player behavior in strategic games, especially complex ones like chess, presents a significant challenge. The difficulty arises from several factors. First, the sheer number of potential outcomes stemming from even a single…

Machine Learning · Computer Science 2025-04-09 Benny Skidanov , Daniel Erbesfeld , Gera Weiss , Achiya Elyasaf

Soccer is a sparse rewarding game: any smart or careless action in critical situations can change the result of the match. Therefore players, coaches, and scouts are all curious about the best action to be performed in critical situations,…

Machine Learning · Computer Science 2021-09-15 Pegah Rahimian , Afshin Oroojlooy , Laszlo Toka

This paper describes the applications of network methods for understanding interaction within members of sport teams.We analyze the interaction of batsmen in International Cricket matches. We generate batting partnership network (BPN) for…

Physics and Society · Physics 2015-03-20 Satyam Mukherjee

Deep neural networks (DNNs) may outperform human brains in complex tasks, but the lack of transparency in their decision-making processes makes us question whether we could fully trust DNNs with high stakes problems. As DNNs' operations…

Machine Learning · Computer Science 2020-03-19 Jung Hoon Lee

This work presents an analysis of the Duckworth-Lewis-Stern (DLS) method for One Day International (ODI) cricket matches. The accuracy of the DLS method is compared against various supervised learning algorithms for result prediction. The…

Machine Learning · Computer Science 2021-06-02 Kumail Abbas , Sajjad Haider

Datascouting is one of the most known data applications in professional sport, and specifically football. Its objective is to analyze huge database of players in order to detect high potentials that can be then individually considered by…

Machine Learning · Computer Science 2024-03-15 Simon Lacan

Over the years, the concept of leadership has experienced a paradigm shift - from solitary leader (centralized leadership) to de-centralized leadership or distributed leadership. This paper explores the idea that centralized leadership, as…

Social and Information Networks · Computer Science 2016-06-17 Satyam Mukherjee

Accurate prediction of FIFA World Cup match outcomes holds significant value for analysts, coaches, bettors, and fans. This paper presents a machine learning framework specifically designed to forecast match winners in FIFA World Cup. By…

Machine Learning · Computer Science 2026-01-07 Ali Al-Bustami , Zaid Ghazal

Opponent modeling is necessary in multi-agent settings where secondary agents with competing goals also adapt their strategies, yet it remains challenging because strategies interact with each other and change. Most previous work focuses on…

Machine Learning · Computer Science 2016-09-20 He He , Jordan Boyd-Graber , Kevin Kwok , Hal Daumé

Twenty20 cricket, sometimes written Twenty-20, and often abbreviated to T20, is a short form of cricket. In a Twenty20 game the two teams of 11 players have a single innings each, which is restricted to a maximum of 20 overs. This version…

Machine Learning · Computer Science 2023-07-25 Ashish V Shenoy , Arjun Singhvi , Shruthi Racha , Srinivas Tunuguntla

In the sport of cricket, player batting ability is traditionally measured using the batting average. However, the batting average fails to measure both short-term changes in ability that occur during an innings, and long-term changes that…

Applications · Statistics 2021-03-25 Oliver George Stevenson , Brendon James Brewer

Devising player-specific strategies in cricket necessitates a meticulous understanding of each player's unique strengths and weaknesses. Nevertheless, the absence of a definitive computational approach to extract such insights from cricket…

Machine Learning · Computer Science 2023-11-14 Swarup Ranjan Behera , Vijaya V. Saradhi

In Major League Baseball, strategy and planning are major factors in determining the outcome of a game. Previous studies have aided this by building machine learning models for predicting the winning team of any given game. We extend this…

Machine Learning · Computer Science 2025-11-05 Morgan Allen , Paul Savala

We demonstrate in this paper the use of tools of complex network theory to describe the strategy of Australia and England in the recently concluded Ashes 2013 Test series. Using partnership data made available by cricinfo during the Ashes…

Physics and Society · Physics 2013-08-27 Satyam Mukherjee

In the sport of cricket, variations in a player's batting ability can usually be measured on one of two scales. Short-term changes in ability that are observed during a single innings, and long-term changes that are witnessed between…

Applications · Statistics 2019-03-19 Oliver G. Stevenson , Brendon J. Brewer

Football forecasting models traditionally rate teams on past match results, that is based on the number of goals scored. Goals, however, involve a high element of chance and thus past results often do not reflect the performances of the…

Applications · Statistics 2021-01-07 Edward Wheatcroft , Ewelina Sienkiewicz