Ranking the Greatest Nba Players: A Sport Metrics Analysis

Mertz, Jeremy; Hoover, Laurie; Burke, Jean Marie; Bellar, David; Jones, Megan L.; Leitzelar, Briana; Judge, W. Lawrence

doi:10.1080/24748668.2016.11868925

Cited by 10 publications

(8 citation statements)

References 1 publication

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“…The comparison of the 28 pairwise of the 8 characteristic objects were executed. Consequently, the Matrix of Expert Judgment (MEJ) was defined as (18), where each α ij value was calculated using Equation (11).…”

Section: Final Modelmentioning

confidence: 99%

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Identification of Players Ranking in E-Sport

2020

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Human activity is moving steadily to virtual reality. More and more, people from all over the world are keen on growing fascination with e-sport. In practice, e-sport is a type of sport in which players compete using computer games. The competitions in games, like FIFA, Dota2, the League of Legends, and Counter-Strike, are prestigious tournaments with a global reach and a budget of millions of dollars. On the other hand, reliable player ranking is a critical issue in both classic and e-sport. For example, the “Golden Ball” is the most valuable prize for an individual football player in the whole football history. Moreover, the entire players’ world wants to know who the best player is. The position of each player in the ranking depends on the assessment of his skills and predispositions. In this paper, we studied identification of players evaluation and ranking obtained using the multiple-criteria decision-making based method called Characteristic Objects METhod (COMET) on the example of the popular game Counter-Strike: Global Offensive (CS: GO). We present a range of advantages of the player evaluation model created using the COMET method and, therefore, prove the practicality of using multi-criteria decision analysis (MCDA) methods to build multi-criteria assessment models in emerging areas of eSports. Thus, we provide a methodical and practical background for building a decision support system engine for the evaluation of players in several eSports.

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Section: Final Modelmentioning

confidence: 99%

“…The accurate player ranking is a crucial issue in both classic [18] and e-sport [19,20]. The result of a classification, calculated based on wins and losses in a competitive game, is often considered to be an indicator of a player's skills [20].…”

Section: Introductionmentioning

confidence: 99%

Identification of Players Ranking in E-Sport

2020

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“…Ranking models have been applied in the ranking of NBA basketball players [28], college sport coaches [19], alternatives in sports tournaments, products, political candidates [6], and others such as the PageRank algorithm introduced by Google [21]. The main aim of this study is to evaluate existing ranking models that may be used for student feedback and to develop an improved ranking feedback model by implementing mathematical programming techniques in three interrelated algorithms.…”

Section: Introductionmentioning

confidence: 99%

Mathematical modelling for academic performance status reports in learning analytics

Merwe

Kruger

Toit

2018

ORiON

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The fast changing nature of the educational environment and the subsequent increase in the volumes of generated learner data, have found existing data analysis techniques lacking in certain fields. These techniques form part of the analysis and reporting phases of learning analytics and need to adapt to accommodate the changing face of education. In this paper, a set of interrelated algorithmic solutions that utilise mathematical programming models to generate and provide learning feedback in the form of academic performance status reports, is presented. Three existing mathematical models, more specifically the benchMark program, an outputs-only data envelopment analysis and a traditional analytic hierarchy process were evaluated for providing the information required to assist students in improving their academic achievement. The requirements include providing students with their current academic performance status, setting interim improvement goals and calculating improvement targets towards reaching those goals. The evaluated models did not address the requirements satisfactorily. The solution proposed in this paper consists of an algorithm that implements a linear programming model to generate performance status reports based on the current assessment scores of a group of students in a module. The output is used in a second algorithm that utilises the remaining improvement opportunities available to generate a participation future time perspective. The resulting schedule together with each individual student's current assessment scores, is used to calculate discrete improvement goals for each student as well as targets towards reaching those goals. A third algorithm provides a lecturer with some insight into the mastering of module content.

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“…Although the selection of the adequate or more representative indices is highly interesting in sport science, as stated in [19], computing an global efficiency index is difficult due to the variety of individual statistics. In [26], the authors recommen to limit the use of individual statistics for predicting the final ranking of their teams.…”

Section: Introductionmentioning

confidence: 99%

A Multicriteria Selection System Based on Player Performance: Case Study—The Spanish ACB Basketball League

2018

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In this paper, we describe an approach to rank sport players based on their efficiency. Although is extremely useful to analyze the performance of team games there is no unanimity on the use of a single index to perform such a ranking. We propose a method to summarize the huge amount of information collected at different aspects of a sport team which is almost daily publicly available. The tool will allow agents involved in a player's negotiation to show the strengths (and weaknesses) of the player with respect to other players. The approach is based on applying a multicriteria outranking methodology using as alternatives the potential players and criteria different efficiency indices. A novel automatic parameter tuning approach is detailed that will allow coaches and sports managers to design templates and sports strategies that improve the efficiency of their teams. We report the results performed over the available information on the ACB Basketball League, and we show how it can be easily implemented and interpreted in practice by decision-makers non familiar with the mathematical side of the methodology.2010 Mathematics Subject Classification. 90B50,62F07,97M40 .

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Ranking the Greatest Nba Players: A Sport Metrics Analysis

Cited by 10 publications

References 1 publication

Identification of Players Ranking in E-Sport

Identification of Players Ranking in E-Sport

Mathematical modelling for academic performance status reports in learning analytics

A Multicriteria Selection System Based on Player Performance: Case Study—The Spanish ACB Basketball League

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