A team recommendation system and outcome prediction for the game of cricket
TLDR
A supervised learning method using SVM model with linear, and nonlinear poly and RBF kernals to predict the outcome of the game against particular side by grouping the players at different levels in the order of play for both the teams and develops a system which recommends a player for a specific role in a team by considering the past performances.About:
This article is published in Journal of Systems Architecture.The article was published on 2018-01-01 and is currently open access. It has received 34 citations till now.read more
Citations
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Journal ArticleDOI
Artificial intelligence for team sports: a survey
TL;DR: Assessing the work in how AI is used to predict match outcomes and to help sports teams improve their strategic and tactical decision making in team sports highlights not only a number of strengths but also weaknesses of the models and techniques that have been employed.
Journal ArticleDOI
Classification of all-rounders in limited over cricket - a machine learning approach
TL;DR: While all the six methods performed well, logistic regression, linear discriminant function, quadratic discriminant functions, and support vector machine showed outstanding performance suggesting that these methods can be used to develop an automated classification rule to classify all-rounders in cricket.
Book ChapterDOI
A Study on Machine Learning Methods Used for Team Formation and Winner Prediction in Cricket
Manoj S. Ishi,J. B. Patil +1 more
TL;DR: In this paper, the study of some existing methods used for team formation and winner prediction in cricket matches is done, which is useful for team management and captain for the selection of players.
Journal ArticleDOI
How Is the Stroke? Inferring Shot Influence in Badminton Matches via Long Short-term Dependencies
TL;DR: A badminton language is introduced to fully describe the process of the shot, and a deep learning model composed of a novel short-term extractor and a long-term encoder is proposed for capturing a shot-by-shot sequence in abadminton rally by framing the problem as predicting a rally result.
Book ChapterDOI
A Survey on Predicting Player’s Performance and Team Recommendation in Game of Cricket Using Machine Learning
Milon Biswas,Tajim Md. Niamat Ullah Akhund,Md. Kawsher Mahbub,Sikder Md. Saiful Islam,Sadia Sorna,M. Shamim Kaiser +5 more
TL;DR: In this paper, the authors explored the techniques that have been applied to solve the challenges in cricket and found that machine learning algorithms like linear regression, support vector machine, random forest, and naive Bayes with linear and polynomial kernel showed good results to predict the runs scored by a batsman and runs given by a bowler.
References
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Journal Article
Predicting the match outcome in one day international cricket matches, while the game is in progress
Michael Bailey,Stephen R. Clarke +1 more
TL;DR: Preliminary results suggest that the market is prone to overreact to events occurring throughout the course of the match, thus creating brief inefficiencies in the wagering market.
Journal ArticleDOI
Optimal batting orders in one-day cricket
TL;DR: The methods developed in the paper are applied to the national team of India based on their performance in one-day intemational cricket matches based on the state of the match and estimated characteristics of individual batsmen.
Proceedings ArticleDOI
CricAI: A classification based tool to predict the outcome in ODI cricket
TL;DR: This work has used artificial intelligence techniques, more specifically Bayesian classifiers in machine learning, to predict how factors related to scoring as well as physical strength affect the outcome of an ODI cricket match and developed a software tool called CricAI, which outputs the probability of victory in an Odi cricket match.
Journal ArticleDOI
A measure for the batting performance of cricket players : research article
TL;DR: In this article, a single measure that can be used to assess the performance of batsmen in cricket is defined and a classification scheme with ten classes according to which batsmen can be classified is given.
Journal ArticleDOI
Forecasting test cricket match outcomes in play
Sohail Akhtar,Philip A. Scarf +1 more
TL;DR: In this article, the authors used a sequence of multinomial logistic regression models to forecast match outcomes in test cricket in play, session by session, and investigated how the outcome probabilities (of a win, draw, or loss) and covariate effects vary session-by-session.
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Applications of Modern Classification Techniques to Predict the Outcome of ODI Cricket
Neeraj Pathak,Hardik Wadhwa +1 more