Quantitative Analysis of Penalty Kicks and Yellow Card Referee Decisions in Soccer

Jimmy Tanamati Soares; Lior Shamir

doi:doi:10.11648/j.ajss.20160405.12

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Quantitative Analysis of Penalty Kicks and Yellow Card Referee Decisions in Soccer

Jimmy Tanamati Soares, Lior Shamir

Published in American Journal of Sports Science (Volume 4, Issue 5)

Received: 1 August 2016 Accepted: 15 August 2016 Published: 29 August 2016

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Abstract

Soccer referees are required to make instant decisions during the game under non-optimal conditions such as imperfect view of the incident and substantial pressure from the crowd, the teams, and the media. Some of the decisions can be subjective, such as a yellow card decision after a foul is called, where different referees might make different decisions. Here we perform quantitative analysis of factors related to the reputation of the team such as the team’s rank, budget, and crowd attendance in home games, and correlate these factors with referee decisions such as penalty kicks and yellow cards. The calls were normalized by dividing the number of yellow cards by the number of fouls, and the number of penalty kicks by the number of shot attempts from the penalty box. Application of the analysis to the four major soccer leagues shows that certain referee decisions have significant correlation with factors such as the team’s rank, budget, and audience in home games, while for other decisions the Pearson correlation is not statistically significant. For budget, or audience in home games. On the other hand, a significant Pearson correlation has been identified between the chance of a foul call to result in a yellow card and the rank or budget of the team in the Bundesliga. The strongest correlation has been observed between the chance of a tackle to result in a foul call, and the budget and rank of the team.

Published in	American Journal of Sports Science (Volume 4, Issue 5)
DOI	10.11648/j.ajss.20160405.12
Page(s)	84-89
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Soccer, Football, Referee, Referee Decisions, Referee Bias

References

[1]	S. Joseph, “A dynamic and psychosocial analysis of soccer: Problems and solutions,” International Journal of Soccer, vol. 1, no. 1, 2015.
[2]	A. J. Picazo-Tadeo, F. Gonzalez G´ omez,´ and J. Guardiola, “The importance of time in referee home bias due to social pressure: evidence from spanish football,” 2011.
[3]	J. Mallo, P. G. Frutos, D. Juarez, and´ E. Navarro, “Effect of positioning on the accuracy of decision making of association football top-class referees and assistant referees during competitive matches,” Journal of Sports Sciences, vol. 30, no. 13, pp. 1437–1445, 2012.
[4]	P. Catteeuw, W. Helsen, B. Gilis, and J. Wagemans, “Decision-making skills, role specificity, and deliberate practice in association football refereeing,” Journal of Sports Sciences, vol. 27, no. 11, pp. 1125– 1136, 2009.
[5]	A. M. Lane, A. M. Nevill, N. S. Ahmad, and N. Balmer, “Soccer referee decisionmaking: shall i blow the whistle?,” Journal of Sports Science & Medicine, vol. 5, no. 2, p. 243, 2006.
[6]	M. Friman, C. Nyberg, and T. Norlander, “Threats and aggression directed at soccer referees: An empirical phenomenological psychological study,” The qualitative report, vol. 9, no. 4, pp. 652–672, 2004.
[7]	M. Fothergill and S. Wolfson, “A comparison of illusory superiority in elite and county uk soccer referees,” International Journal of Sport Psychology, vol. 46, no. 5, 2015.
[8]	R. R. Oudejans, R. Verheijen, F. C. Bakker, J. C. Gerrits, M. Steinbruckner, and P. J.¨ Beek, “Errors in judging offside in football,” Nature, vol. 404, no. 6773, pp. 33– 33, 2000.
[9]	W. Helsen, B. Gilis, and M. Weston, “Errors in judging offside in association football: Test of the optical error versus the perceptual flash-lag hypothesis,” Journal of Sports Sciences, vol. 24, no. 05, pp. 521–528, 2006.
[10]	S. Sd’ottavio and C. Castagana, “Analysis of match activities in elite soccer referees during actual match play.” The Journal of Strength & Conditioning Research, vol. 15, no. 2, pp. 167–171, 2001.
[11]	M. Weston, C. Castagna, F. M. Impellizzeri, E. Rampinini, and G. Abt, “Analysis of physical match performance in english premier league soccer referees with particular reference to first half and player work rates,” Journal of Science and Medicine in Sport, vol. 10, no. 6, pp. 390– 397, 2007.
[12]	C. Castagana and S. Stefano, “Physiological load imposed on elite soccer referees during actual match play,” Journal of Sports Medicine and Physical Fitness, vol. 41, no. 1, pp. 27–32, 2001.
[13]	C. Castagana, G. Abt, and S. Stefano, “Relation between fitness tests and match performance in elite italian soccer referees.,” The Journal of Strength & Conditioning Research, vol. 16, no. 2, pp. 231–235, 2002.
[14]	T. E. Andersen, L. Engebretsen, and R. Bahr, “Rule violations as a cause of injuries in male norwegian professional football are the referees doing their job?,” The American Journal of Sports Medicine, vol. 32, no. 1 suppl, pp. 62S–68S, 2004.
[15]	C. Fuller, A. Junge, and J. Dvorak, “An assessment of football referees decisions in incidents leading to player injuries,” The American Journal of Sports Medicine, vol. 32, no. 1 suppl, pp. 17S–22S, 2004.
[16]	L. Godinho and C. Barbosa, “Topics for an academic agenda: The prevention of match fixing in brazil,” in Match Fixing in International Sports, pp. 229– 245, Springer, 2013.
[17]	E. Dunning, Sport matters: Sociological studies of sport, violence, and civilization. Psychology Press, 1999.
[18]	S. Colwell, “The letterand the spirit: Football laws and refereeing in the twenty-first century,” Soccer & Society, vol. 1, no. 1, pp. 201–214, 2000.
[19]	S. Gencay, “Magnitude of psychological stress reported by soccer referees,” Social Behavior and Personality: an international journal, vol. 37, no. 7, pp. 865–868, 2009.
[20]	M. Guschwan, “Riot in the curve: Soccer fans in twenty-first century italy,” Soccer & Society, vol. 8, no. 2-3, pp. 250–266, 2007.
[21]	M. V. Jones, G. C. Paull, and J. Erskine, “The impact of a team’s aggressive reputation on the decisions of association football referees,” Journal of Sports Sciences, vol. 20, no. 12, pp. 991–1000, 2002.
[22]	A. M. Nevill, N. J. Balmer, and A. M. Williams, “The influence of crowd noise and experience upon refereeing decisions in football,” Psychology of Sport and Exercise, vol. 3, no. 4, pp. 261–272, 2002.
[23]	P. Downward and M. Jones, “Effects of crowd size on referee decisions: Analysis of the fa cup,” Journal of Sports Sciences, vol. 25, no. 14, pp. 1541–1545, 2007.
[24]	B. Buraimo, D. Forrest, and R. Simmons, “The 12th man?: Refereeing bias in english and german soccer,” Journal of the Royal Statistical Society: Series A, vol. 173, no. 2, pp. 431–449, 2010.
[25]	B. Buraimo, R. Simmons, and M. Maciaszczyk, “Favoritism and referee bias in european soccer: Evidence from the spanish league and the uefa champions league,” Contemporary Economic Policy, vol. 30, no. 3, pp. 329–343, 2012.
[26]	R. H. Boyko, A. R. Boyko, and M. G. Boyko, “Referee bias contributes to home advantage in english premiership football,” Journal of Sports Sciences, vol. 25, no. 11, pp. 1185–1194, 2007.
[27]	R. Pollard, “Home advantage in football: A current review of an unsolved puzzle,” The Open Sports Sciences Journal, vol. 1, no. 1, pp. 12–14, 2008.
[28]	R. Johnston, “On referee bias, crowd size, and home advantage in the english soccer premiership,” Journal of Sports Sciences, vol. 26, no. 6, pp. 563–568, 2008.
[29]	C. Goumas, “Home advantage and referee bias in European football,” European Journal of Sport Science, vol. 14, no. sup 1, pp. S243–S249, 2014.
[30]	V. Scoppa, “Are subjective evaluations biased by social factors or connections? an econometric analysis of soccer referee decisions,” Empirical Economics, vol. 35, no. 1, pp. 123–140, 2008.
[31]	D. Riedl, B. Strauss, A. Heuer, and O. Rubner, “Finale furioso: referee-biased injury times and their effects on home advantage in football,” Journal of Sports Sciences, vol. 33, no. 4, pp. 327–336, 2015.
[32]	B. Reilly and R. Witt, “Red cards, referee home bias and social pressure: evidence from english premiership soccer,” Applied Economics Letters, vol. 20, no. 7, pp. 710–714, 2013.
[33]	M. Anderson, S. Wolfson, N. Neave, and M. Moss, “Perspectives on the home advantage: A comparison of football players, fans and referees,” Psychology of Sport and Exercise, vol. 13, no. 3, pp. 311–316, 2012.
[34]	K. G. Yewell, S. B. Caudill, and F. G. Mixon Jr, “Referee bias and stoppage time in major league soccer: A partially adaptive approach,” Econometrics, vol. 2, no. 1, pp. 1–19, 2014.
[35]	R. Prußner and M. Siegle, “Additional¨ time in soccer–influence of league and referee,” International Journal of Performance Analysis in Sport, vol. 15, no. 2, pp. 551–559, 2015.
[36]	J. Coleclough, “Soccer coaches’ and referees’ perceptions of tackle incidents with respect to the laws of the game,” International Journal of Performance Analysis in Sport, vol. 13, no. 2, pp. 553–566, 2013.
[37]	V. Hlasny and S. Kolaric, “Catch me if you can: Referee-team relationships and disciplinary cautions in football,” Journal of Sports Economics, vol. 1, 2014.
[38]	B. R. Pope and N. G. Pope, “Ownnationality bias: Evidence from uefa champions league football referees,” Economic Inquiry, vol. 53, no. 2, pp. 1292– 1304, 2015.
[39]	S. Pohlkamp, “The impact of referees on match outcomes in professional sports: Evidence from the german football bundesliga,” 2013.
[40]	S. Mancini and A. Isabello, “Fair referee assignment for the italian soccer seriea,” Journal of Quantitative Analysis in Sports, vol. 10, no. 2, pp. 153–160, 2014.
[41]	F. Gonzalez-G´ omez and A. J. Picazo-´ Tadeo, “Can we be satisfied with our football team? evidence from spanish professional football,” Journal of Sports Economics, vol. 11, no. 4, pp. 418–442, 2010.
[42]	J. Oberstone, “Comparing team performance of the english premier league, serie a, and la liga for the 2008-2009 season,” Journal of Quantitative Analysis in Sports, vol. 7, no. 1, 2011.
[43]	C. Carling, F. Le Gall, A. McCall, M. Ned´ elec, and G. Dupont, “Squad man-´ agement, injury and match performance in a professional soccer team over a championship-winning season,” European journal of sport science, no. ahead-ofprint, pp. 1–10, 2014.
[44]	J. Vecer, F. Kopriva, and T. Ichiba, “Estimating the effect of the red card in soccer: when to commit an offense in exchange for preventing a goal opportunity,” Journal of Quantitative Analysis in Sports, vol. 5, no. 1, 2009.
[45]	K. Radnedge, The Complete Encyclopedia of Soccer: The Bible of World Soccer. Carlton, 2000.
[46]	R. Henshaw, The encyclopedia of world soccer. New Re, 1979.
[47]	N. Owens, C. Harris, and C. Stennett, “Hawk-eye tennis system,” in IEE Conference Publication, pp. 182–185, Institution of Electrical Engineers, 2003.
[48]	H. M. Collins and R. Evans, “You cannot be serious! public understanding of technology with special reference to hawk-eye,” Public Understanding of Science, 2008.
[49]	H. Collins and R. Evans, “Sport-decision aids and the csi-effect: Why cricket uses hawk-eye well and tennis uses it badly,” Public Understanding of Science, vol. 21, no. 8, pp. 904–921, 2012.
[50]	J. Balko, D. Moffatt, and D. Searcy, “Photo finish record system,” 1974. US Patent 3,829,869.
[51]	N. Ancona, G. Cicirelli, A. Branca, and A. Distante, “Goal detection in football by using support vector machines for classification,” in Proceedings of the International Joint Conference on Neural Networks, vol. 1, pp. 611–616, IEEE, 2001.

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APA Style

Jimmy Tanamati Soares, Lior Shamir. (2016). Quantitative Analysis of Penalty Kicks and Yellow Card Referee Decisions in Soccer. American Journal of Sports Science, 4(5), 84-89. https://doi.org/10.11648/j.ajss.20160405.12

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Jimmy Tanamati Soares; Lior Shamir. Quantitative Analysis of Penalty Kicks and Yellow Card Referee Decisions in Soccer. Am. J. Sports Sci. 2016, 4(5), 84-89. doi: 10.11648/j.ajss.20160405.12

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AMA Style

Jimmy Tanamati Soares, Lior Shamir. Quantitative Analysis of Penalty Kicks and Yellow Card Referee Decisions in Soccer. Am J Sports Sci. 2016;4(5):84-89. doi: 10.11648/j.ajss.20160405.12

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@article{10.11648/j.ajss.20160405.12,
  author = {Jimmy Tanamati Soares and Lior Shamir},
  title = {Quantitative Analysis of Penalty Kicks and Yellow Card Referee Decisions in Soccer},
  journal = {American Journal of Sports Science},
  volume = {4},
  number = {5},
  pages = {84-89},
  doi = {10.11648/j.ajss.20160405.12},
  url = {https://doi.org/10.11648/j.ajss.20160405.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajss.20160405.12},
  abstract = {Soccer referees are required to make instant decisions during the game under non-optimal conditions such as imperfect view of the incident and substantial pressure from the crowd, the teams, and the media. Some of the decisions can be subjective, such as a yellow card decision after a foul is called, where different referees might make different decisions. Here we perform quantitative analysis of factors related to the reputation of the team such as the team’s rank, budget, and crowd attendance in home games, and correlate these factors with referee decisions such as penalty kicks and yellow cards. The calls were normalized by dividing the number of yellow cards by the number of fouls, and the number of penalty kicks by the number of shot attempts from the penalty box. Application of the analysis to the four major soccer leagues shows that certain referee decisions have significant correlation with factors such as the team’s rank, budget, and audience in home games, while for other decisions the Pearson correlation is not statistically significant. For budget, or audience in home games. On the other hand, a significant Pearson correlation has been identified between the chance of a foul call to result in a yellow card and the rank or budget of the team in the Bundesliga. The strongest correlation has been observed between the chance of a tackle to result in a foul call, and the budget and rank of the team.},
 year = {2016}
}

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TY  - JOUR
T1  - Quantitative Analysis of Penalty Kicks and Yellow Card Referee Decisions in Soccer
AU  - Jimmy Tanamati Soares
AU  - Lior Shamir
Y1  - 2016/08/29
PY  - 2016
N1  - https://doi.org/10.11648/j.ajss.20160405.12
DO  - 10.11648/j.ajss.20160405.12
T2  - American Journal of Sports Science
JF  - American Journal of Sports Science
JO  - American Journal of Sports Science
SP  - 84
EP  - 89
PB  - Science Publishing Group
SN  - 2330-8540
UR  - https://doi.org/10.11648/j.ajss.20160405.12
AB  - Soccer referees are required to make instant decisions during the game under non-optimal conditions such as imperfect view of the incident and substantial pressure from the crowd, the teams, and the media. Some of the decisions can be subjective, such as a yellow card decision after a foul is called, where different referees might make different decisions. Here we perform quantitative analysis of factors related to the reputation of the team such as the team’s rank, budget, and crowd attendance in home games, and correlate these factors with referee decisions such as penalty kicks and yellow cards. The calls were normalized by dividing the number of yellow cards by the number of fouls, and the number of penalty kicks by the number of shot attempts from the penalty box. Application of the analysis to the four major soccer leagues shows that certain referee decisions have significant correlation with factors such as the team’s rank, budget, and audience in home games, while for other decisions the Pearson correlation is not statistically significant. For budget, or audience in home games. On the other hand, a significant Pearson correlation has been identified between the chance of a foul call to result in a yellow card and the rank or budget of the team in the Bundesliga. The strongest correlation has been observed between the chance of a tackle to result in a foul call, and the budget and rank of the team.
VL  - 4
IS  - 5
ER  -

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Author Information

Jimmy Tanamati Soares

Department of Comp. Sci., Lawrence Technological University, Southfield, MI, USA
Lior Shamir

Department of Comp. Sci., Lawrence Technological University, Southfield, MI, USA

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APA Style

Jimmy Tanamati Soares, Lior Shamir. (2016). Quantitative Analysis of Penalty Kicks and Yellow Card Referee Decisions in Soccer. American Journal of Sports Science, 4(5), 84-89. https://doi.org/10.11648/j.ajss.20160405.12

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ACS Style

Jimmy Tanamati Soares; Lior Shamir. Quantitative Analysis of Penalty Kicks and Yellow Card Referee Decisions in Soccer. Am. J. Sports Sci. 2016, 4(5), 84-89. doi: 10.11648/j.ajss.20160405.12

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AMA Style

Jimmy Tanamati Soares, Lior Shamir. Quantitative Analysis of Penalty Kicks and Yellow Card Referee Decisions in Soccer. Am J Sports Sci. 2016;4(5):84-89. doi: 10.11648/j.ajss.20160405.12

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@article{10.11648/j.ajss.20160405.12,
  author = {Jimmy Tanamati Soares and Lior Shamir},
  title = {Quantitative Analysis of Penalty Kicks and Yellow Card Referee Decisions in Soccer},
  journal = {American Journal of Sports Science},
  volume = {4},
  number = {5},
  pages = {84-89},
  doi = {10.11648/j.ajss.20160405.12},
  url = {https://doi.org/10.11648/j.ajss.20160405.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajss.20160405.12},
  abstract = {Soccer referees are required to make instant decisions during the game under non-optimal conditions such as imperfect view of the incident and substantial pressure from the crowd, the teams, and the media. Some of the decisions can be subjective, such as a yellow card decision after a foul is called, where different referees might make different decisions. Here we perform quantitative analysis of factors related to the reputation of the team such as the team’s rank, budget, and crowd attendance in home games, and correlate these factors with referee decisions such as penalty kicks and yellow cards. The calls were normalized by dividing the number of yellow cards by the number of fouls, and the number of penalty kicks by the number of shot attempts from the penalty box. Application of the analysis to the four major soccer leagues shows that certain referee decisions have significant correlation with factors such as the team’s rank, budget, and audience in home games, while for other decisions the Pearson correlation is not statistically significant. For budget, or audience in home games. On the other hand, a significant Pearson correlation has been identified between the chance of a foul call to result in a yellow card and the rank or budget of the team in the Bundesliga. The strongest correlation has been observed between the chance of a tackle to result in a foul call, and the budget and rank of the team.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - Quantitative Analysis of Penalty Kicks and Yellow Card Referee Decisions in Soccer
AU  - Jimmy Tanamati Soares
AU  - Lior Shamir
Y1  - 2016/08/29
PY  - 2016
N1  - https://doi.org/10.11648/j.ajss.20160405.12
DO  - 10.11648/j.ajss.20160405.12
T2  - American Journal of Sports Science
JF  - American Journal of Sports Science
JO  - American Journal of Sports Science
SP  - 84
EP  - 89
PB  - Science Publishing Group
SN  - 2330-8540
UR  - https://doi.org/10.11648/j.ajss.20160405.12
AB  - Soccer referees are required to make instant decisions during the game under non-optimal conditions such as imperfect view of the incident and substantial pressure from the crowd, the teams, and the media. Some of the decisions can be subjective, such as a yellow card decision after a foul is called, where different referees might make different decisions. Here we perform quantitative analysis of factors related to the reputation of the team such as the team’s rank, budget, and crowd attendance in home games, and correlate these factors with referee decisions such as penalty kicks and yellow cards. The calls were normalized by dividing the number of yellow cards by the number of fouls, and the number of penalty kicks by the number of shot attempts from the penalty box. Application of the analysis to the four major soccer leagues shows that certain referee decisions have significant correlation with factors such as the team’s rank, budget, and audience in home games, while for other decisions the Pearson correlation is not statistically significant. For budget, or audience in home games. On the other hand, a significant Pearson correlation has been identified between the chance of a foul call to result in a yellow card and the rank or budget of the team in the Bundesliga. The strongest correlation has been observed between the chance of a tackle to result in a foul call, and the budget and rank of the team.
VL  - 4
IS  - 5
ER  -

Copy | Download