An innovative super-efficiency data envelopment analysis, semi-variance, and Shannon-entropy-based methodology for player selection: evidence from cricket

Adhikari, Arnab; Majumdar, Adrija; Gupta, Gaurav; Bisi, Arnab

doi:10.1007/s10479-018-3088-4

Cited by 24 publications

(10 citation statements)

References 32 publications

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“…Information entropy was proposed by Shannon in 1948 and used to analyze and study the uncertainty of information through probabilistic methods. The entropy method is an objective weighting method that determines the weight of indicators based on the amount of information contained in each indicator, which can avoid bias due to subjective factors ( 36 ). Evaluation index is n items, the original index data matrix X = (X ij ) m×n is obtained.…”

Section: Methodsmentioning

confidence: 99%

Measurement of Agricultural Green Development Level in the Three Provinces of Northeast China Under the Background of Rural Vitalization Strategy

Hou

Wang

2022

Front. Public Health

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This paper offers an evaluation index system of agricultural green development level based on the Rural Vitalization Strategy. The evaluation index system includes four dimensions: agricultural development, ecological resource protection, environment-friendly, and industrial extension and integration. Then, the paper calculates the level of agricultural green development in the three provinces of Northeast China using the entropy-gray correlation method from 2009 to 2019. The calculation results show that between 2009 and 2019, the level of agricultural green development in the three northeastern provinces of China fluctuates and increases, and there is some variation between them: in terms of the overall level of agricultural green development Heilongjiang Province > Liaoning Province > Jilin Province, in terms of the average change speed of agricultural green development level, Heilongjiang Province > Liaoning Province > Jilin Province; in terms of each dimension, the average level of correlation degree of agricultural development dimension is Liaoning Province > Heilongjiang Province > Jilin Province, the average level of correlation degree of ecological resource protection dimension is Heilongjiang Province > Jilin Province > Liaoning Province, the average level of correlation degree of environment-friendly dimension is Heilongjiang Province > Jilin Province > Liaoning Province, and the average level of correlation degree of industrial extension and integration is Liaoning Province > Heilongjiang Province > Jilin Province. Finally, the basis of the calculation results, combined with the actual situation of agricultural development in the three provinces, the countermeasures, and suggestions for promoting the green development of agriculture are put forward. Specifically, it includes the establishment of an evaluation system for agricultural green development; strengthening the protection of agricultural ecological resources; increasing rural environmental governance; promoting the integrated development of rural tertiary industries; vigorously supporting agricultural scientific and technological innovation; and strengthening regional cooperation and other suggestions.

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Section: Methodsmentioning

confidence: 99%

Measurement of Agricultural Green Development Level in the Three Provinces of Northeast China Under the Background of Rural Vitalization Strategy

Hou

Wang

2022

Front. Public Health

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“…Van Bulck et al (2019) consider a tabu search based approach by scheduling a non-professional indoor football league. Adhikari et al (2020) propose a methodology for cricket player selection based on an efficiency data envelopment analysis, semi-variance approach, and Shannon-entropy. Cea et al (2020) analyze the procedure used by FIFA up until 2018 to rank national football teams Papers specifically on clustering of sports data are Gates et al (2017), Behravan and Razavi (2021), Fortuna et al (2018), Lu and Tan (2003), Narizuka and Yamazaki (2019), Narizuka and Yamazaki (2020), Shelly et al (2020), Ulas (2021), most of which with applications to football data.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

A robust method for clustering football players with mixed attributes

2022

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A robust fuzzy clustering model for mixed data is proposed. For each variable, or attribute, a proper dissimilarity measure is computed and the clustering procedure combines the dissimilarity matrices with weights objectively computed during the optimization process. The weights reflect the relevance of each attribute type in the clustering results. A simulation study and an empirical application to football players data are presented that show the effectiveness of the proposed clustering algorithm in finding clusters that would be hidden unless a multi-attributes approach were used.

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“…The development of advanced statistical methods to forecast teams and players' performances (e.g. Adhikari et al 2020;Galariotis et al 2018;Yang et al 2014) or match results (e.g. Diniz et al 2019;Friesl et al 2020;Koopman and Lit 2015;Nikolaidis 2015) has recently attracted the interest of many researchers in the field of statistics and econometrics.…”

Section: Introductionmentioning

confidence: 99%

Forecasting binary outcomes in soccer

Mattera

2021

Ann Oper Res

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Several studies deal with the development of advanced statistical methods for predicting football match results. These predictions are then used to construct profitable betting strategies. Even if the most popular bets are based on whether one expects that a team will win, lose, or draw in the next game, nowadays a variety of other outcomes are available for betting purposes. While some of these events are binary in nature (e.g. the red cards occurrence), others can be seen as binary outcomes. In this paper we propose a simple framework, based on score-driven models, able to obtain accurate forecasts for binary outcomes in soccer matches. To show the usefulness of the proposed statistical approach, two experiments to the English Premier League and to the Italian Serie A are provided for predicting red cards occurrence, Under/Over and Goal/No Goal events.

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An innovative super-efficiency data envelopment analysis, semi-variance, and Shannon-entropy-based methodology for player selection: evidence from cricket

Cited by 24 publications

References 32 publications

Measurement of Agricultural Green Development Level in the Three Provinces of Northeast China Under the Background of Rural Vitalization Strategy

Measurement of Agricultural Green Development Level in the Three Provinces of Northeast China Under the Background of Rural Vitalization Strategy

A robust method for clustering football players with mixed attributes

Forecasting binary outcomes in soccer

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