Measuring Technical Efficiency in Sports

Collier, Trevor; Johnson, Andrew L.; Ruggiero, John

doi:10.1177/1527002510391582

Cited by 22 publications

(23 citation statements)

References 27 publications

(29 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this case, this soccer team would have avoided relegation to the secondary league, in which Kalloni (#12) would have ended up. Fourth, OSFP (#1) and Aris (#18) proved to be athletically efficient irrespective of whether they were evaluated by (1), the proportional output reduction strategy of Lins et al (2003) or the equal output reduction strategy of Collier et al (2011). This is because OSFP (#1) cumulated the most points in the league season under consideration and Aris (#18) some points despite scoring the fewest goals.…”

Section: Second Soccer Teams Under Evaluation Could Potentially Havementioning

confidence: 99%

“…Consequently, , + , and , may be biased downward and, for this reason, we have to adjust them by following Bouzidis and Karagiannis (2019). For robustness purposes, this adjustment is achieved by means of both the proportional output reduction strategy of Lins et al (2003) and the equal output reduction strategy of Collier et al (2011).…”

Section: Offensementioning

confidence: 99%

“…To understand how this is possible, consider that a soccer team would be actually benefited by exchanging, for example, two of its (1-1) ties for a (2-0) victory and a (0-2) loss. Third, had it been athletically efficient, Apollon Athens (#17) could have been placed tenth (according to the results provided by (1) and the equal output reduction strategy of Collier et al, 2011). In this case, this soccer team would have avoided relegation to the secondary league, in which Kalloni (#12) would have ended up.…”

Section: Second Soccer Teams Under Evaluation Could Potentially Havementioning

confidence: 99%

“…3) ℎ 1 and , 3 were provided by the equal output reduction strategy of Collier et al (2011). Notes: 1) ℎ was produced by (1), 2) ℎ 0 was provided by the proportional output reduction strategy of Lins et al (2003), Fifth, the top five soccer teams in the final ranking cumulated points more efficiently than their direct competitors during the league season under consideration.…”

Section: Second Soccer Teams Under Evaluation Could Potentially Havementioning

confidence: 99%

See 3 more Smart Citations

On-field Performance Evaluation in Soccer Based on Network Data Envelopment Analysis

Bouzidis

2019

DEA

View full text Add to dashboard Cite

In this paper, we present for the first time the on-field production process of soccer teams as a mixed (serial and parallel) structure two-stage network system. According to this, the first stage consists of two distinct sub-processes (offense and defense) that operate in parallel. These respectively use players' offensive and defensive actions as inputs to produce two different intermediate measures, namely, goals scored and prevention of goals conceded. These, in turn, are the inputs of the second stage (points' accumulation sub-process) that produces accumulated points. Furthermore, based on a two-stage network Data Envelopment Analysis (DEA) model, we estimate the offensive, defensive, and athletic efficiency of soccer teams during a league season.According to our proposed framework, these three different efficiency scores are provided (for each soccer team under evaluation) by a single linear programming problem. For this purpose, aggregate-over-games statistics from the 2013-14 Greek premier soccer league are used. IntroductionSince the study of Carmichael et al. (2001), on-field performance evaluation in soccer seeks to answer whether athletic efficiency leads teams to sporting success. To this end, Espitia-Escuer and García-Cebrián (2004, 2006 proposed to estimate the athletic efficiency of soccer teams during a league season based on a single-stage Data Envelopment Analysis (DEA) model. According to this model, the on-field actions of soccer teams are considered as inputs and their accumulated points as a single output. This variable is preferred over the number of teams' victories (or their winning percentage) during a league season (Dawson et al., 2000, p. 407). This is due to the fact that (in each soccer game) there are three probable results, each of which is rewarded differently. In particular, victories (losses) receive three (zero) points and ties one point for each soccer team. Some years later, the studies of Boscá et al. (2009) andSala-Garrido et al. (2009) took a step further in the on-field performance evaluation of soccer teams. Specifically, these studies proposed to separately estimate the offensive and defensive efficiency of soccer teams during a league season based on two different single-stage DEA models.According to these models, teams' goals scored and the inverse of teams' goals conceded are independently used as a single output. In this way, the above studies

show abstract

Section: Second Soccer Teams Under Evaluation Could Potentially Havementioning

confidence: 99%

Section: Offensementioning

confidence: 99%

Section: Second Soccer Teams Under Evaluation Could Potentially Havementioning

confidence: 99%

Section: Second Soccer Teams Under Evaluation Could Potentially Havementioning

confidence: 99%

See 2 more Smart Citations

On-field Performance Evaluation in Soccer Based on Network Data Envelopment Analysis

Bouzidis

2019

DEA

View full text Add to dashboard Cite

show abstract

“…Examples of football performance evaluation are [9][10][11][12]. Moreover, Tiedemann et al [13] focused on a performance of football players instead of the whole clubs.…”

Section: Measuring Efficiency and Performance In Footballmentioning

confidence: 99%

Performance Analysis During the 2014 FIFA World Cup Qualification

Flégl¹

2014

TOSSJ

View full text Add to dashboard Cite

This article analyzes the performance of the national football teams during the 2014 FIFA World Cup qualification. The sample consists of 31 qualified national teams to the final tournament in Brazil. The analysis uses Data Envelopment Analysis (DEA) methodology and is carried out for the whole qualification period between June 2011 and November 2013. Each national team is evaluated according to a number of played matches, used players, qualification group quality, obtained points, and score. The results show that only 12.9% teams reached the performance of 100%. The reasons of low performances mainly depend on teams´ qualities either in each qualification zone or in each qualification group. In addition, a sensitivity analysis is used to confirm the adequate structure of the DEA model.

show abstract

Multiobjective centralized DEA approach to Tokyo 2020 Olympic Games

Lozano

Villa

2022

Ann Oper Res

View full text Add to dashboard Cite

There exist two types of Data Envelopment Analysis (DEA) approaches to the Olympic Games: conventional and fixed-sum outputs (FSO). The approach proposed in this paper belongs to the latter category as it takes into account the total number de medals of each type awarded. Imposing these constraints requires a centralized DEA perspective that projects all the countries simultaneously. In this paper, a multiobjective FSO approach is proposed, and the Weighted Tchebychef solution method is employed. This approach aims to set all output targets as close as possible to their ideal values. In order to choose between the alternative optima, a secondary goal has been considered that minimizes the sum of absolute changes in the number of medals, which also renders the computed targets to be as close to the observed values as possible. These targets represent the output levels that could be expected if all countries performed at their best level. For certain countries, the targets are higher than the actual number of medals won while, for other countries, these targets may be lower. The proposed approach has been applied to the results of the Tokyo 2020 Olympic Games and compared with both FSO and non-FSO DEA methods.

show abstract

Measuring Technical Efficiency in Sports

Cited by 22 publications

References 27 publications

On-field Performance Evaluation in Soccer Based on Network Data Envelopment Analysis

On-field Performance Evaluation in Soccer Based on Network Data Envelopment Analysis

Performance Analysis During the 2014 FIFA World Cup Qualification

Multiobjective centralized DEA approach to Tokyo 2020 Olympic Games

Contact Info

Product

Resources

About