Cheating In Soccer: Team culture, player behaviour



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  • Cheating In Soccer:
  • Team culture, player behaviour
  • or just a question of circumstance?
  • Chris Stride
  • Malcolm Patterson
  • Ffion Thomas
  • University of Sheffield
  • UK
  • Cheating in professional soccer generates heightened emotions and meanings…
  • “The Football Association of Ireland (FAI) lodged a formal complaint with FIFA and demanded that their controversial World Cup play-off defeat by France last night should be replayed. The FAI acted after Irish justice minister Dermot Ahern urged them to make an official protest following the 2-1 aggregate defeat.”
  • “He said: ‘If that result remains,
  • it reinforces the view that if
  • you cheat you will win.’”
  • Why and when do professional
  • soccer players engage in
  • cheating behaviours?
  • Study Outline
  • Classifying types of cheating within soccer.
  • Counting the occurrences of each type of cheating within a soccer tournament likely to feature varying levels of a range of player, team and match characteristics.
  • Investigating whether the amount of cheating of different types varies by player, team and match.
  • Investigating whether and if so which characteristics of players, teams or matches explain this variation.
  • What is Cheating?
  • “Cheating is… to act fraudulently, to deceive, swindle, or flout rules designed to maintain conditions of fairness.”
  • Cashmore (2000)
  • In the context of sport…
  • “The rules of football and chess… do not just regulate playing football and chess, but create the very possibility of playing such games.”
  • Searle (1969)
  • What is Cheating?
  • Sports are effectively governed by their ethos, which takes on the constitutive function:
    • Shared set of norms for the interpretation of key constitutive rules (D’Agostino, 1981).
  • Sharing norms does not imply perfect agreement:
    • Soccer players may differ on perceived morality of professional foul.
    • “Every sport competition can be seen as a verbal and embodied discourse in which shared norms for the interpretation of the rules are challenged, negotiated and adjusted.” (Loland et al, 2000)
  • What is Cheating?
  • Cheating (‘intentional ethos violation’) was classified by Loland (2005):
    • Classic cheating: involves deceit, can have single or multiple advantageous consequences. A subtype is simulation or ‘play-acting’, which typically has multiple advantageous consequences.
    • Tactical / professional fouls; deceit plays no part. Penalty accepted, long-term benefit. Arguably a rule violation but not an ethos violation in soccer?
  • We implemented Loland’s typology in the context of soccer.
  • A Typology of Cheating within Soccer
  • Classic Cheating: Simulation or ‘play-acting’, typically multiple advantageous consequences.
    • Simulation of being fouled (i.e. diving) inside the penalty area.
    • Simulation of being fouled (i.e. diving) outside of the penalty area.
    • Exaggerating an injury received from a foul tackle to get opponent punished.
    • Simulation of being assaulted.
    • Time-wasting by faking or exaggerating the severity of an injury.
  • A Typology of Cheating within Soccer
  • Classic Cheating: single consequence.
    • Deliberate handball to score goal.
    • Deliberate handball to progress attack.
    • Attempting to 'steal' extra yards or more at a free kick, encroachment by attacking side at a penalty kick.
  • A Typology of Cheating within Soccer
  • Tactical or professional fouls: Fouling
    • Fouling a player to prevent clear goal scoring opportunity.
    • Fouling a player to prevent an attack continuing.
  • Tactical or professional fouls: Handball
    • Deliberate handball to prevent goal.
    • Deliberate handball to prevent attack continuing, but not yet clear goal scoring opportunity.
  • A Typology of Cheating within Soccer
  • Tactical or professional fouls: Time-wasting/encroachment
    • Time-wasting; kicking ball away.
    • Time-wasting; taking too long to leave pitch, take free kick, etc.
    • Stopping the opposition taking a quick free-kick by kicking ball away or holding on to it, or encroachment by defending side at a free kick or penalty kick.
  • A Typology of Cheating within Soccer
  • What we didn’t consider as cheating…
    • Rule violations that are definitely not ethos violations i.e. are part of the ethos though technically against the laws. Jostling, mutual shirt-pulling, defender climbing / forward backing in situations…“It’s a mans’ game!”
    • Intentional rule violations due to a player losing his temper i.e. where we judged there to be no apparent calculation of the cost or any intention to deceive.
    • Unintentional violations e.g. offside, mistimed tackles.
    • Passive cheating: not informing the officials of a mistake they have made e.g. ball crossing the line.
  • Why Variation in Cheating May Occur
  • Variation in the amount of cheating in a tournament may exist…
    • within matches, (not yet considered in this study)
    • between players,
    • between teams,
    • between matches.
  • Why Variation in Cheating May Occur
  • Between player variation in cheating:
    • Mental causes (Hard to measure/find measures of)
      • Moral identity/moral functioning (Rest, 1984).
      • Legitimacy judgement/acceptance of cheating.
      • Personality (e.g. neuroticism).
      • Motivation: Primary goal perspective; Ego Orientation or Task Orientation (Nicholls, 1984).
      • Experiences of cheating.
    • Physical or Situational causes …
      • Ability, fitness, playing experience and position.
  • Why Variation in Cheating May Occur
  • Between match variation in cheating:
    • Match stressors…
      • Sudden death matches.
      • Rivalry between teams (local or historical, soccer-specific or deeper national conflict).
      • Balance of possession and closeness of match.
    • Referee effects…
      • Law enforcement and interpretation.
      • Experience and competence.
  • Why Variation in Cheating May Occur
  • Between team variation in cheating:
    • Team ability (Nilsson,1993)…
      • Good enough not to need to cheat or so bad that only way to win is by cheating.
      • Pressure to maintain past success.
    • Team ‘climate’ (Hard to measure/find measures of)
      • Collective team climate impacts on moral judgement (e.g., Shields & Bredemeier, 2001).
      • Created by beliefs of members and manager (e.g. Stephens, 2000).
  • Why Variation in Cheating May Occur
  • Between team variation in cheating:
    • National cultural dimensions…
      • Individualism, Masculinity, Power-distance, Uncertainty/Risk-taking Avoidance (Hofstede; 1990, 2003).
      • Culture dimension scores vary by nation (Hofstede, 2003; Ronen & Shenkar, 1985).
      • A team reflects national culture (Schein, 1985).
      • Which if any national cultural dimensions are important in explaining attitudes to cheating?
  • Why Variation in Cheating May Occur
  • Between team variation in cheating:
    • National cultural dimensions…
      • Several studies (e.g. Franke & Nadler, 2008), have found that Power Distance and Uncertainty Avoidance negatively impact ethical behaviour in business.
      • The desire to avoid facing the uncertainty of medium-term events motivates risky (often unethical) behaviour in the short-term.
      • Power distance  “as life is unfair, you might as well take what you can get when you can get it.” (Wilson, 2007)
  • Method
  • We focused on the 2010 World Cup…
    • 64 matches of varying importance.
    • Wide range of player background and team cultures.
    • Feasible to watch and code every game using same coders.
    • Feasible to collect data on objective player, team and match characteristics, and on national cultural dimensions - scores on each Hofstede dimension available for most but not all of WC 2010 nations.
    • Consistent refereeing?
    • Public and official interest.
  • Method
  • Public and official interest:
    • "FIFA strongly opposes any kind of cheating action, including diving, which goes against the spirit of fair play.”
    • “…before the 2002 World Cup referees were ordered to crack down on diving, and the same instruction will be given to referees before this year's finals.”
  • Method
    • Two coders independently watched every match in WC2010, coding and reviewing incidents via internet playback, recording each incident in terms of…
      • The type of cheating and its consequences.
      • The identity of the instigator and victim.
      • The match time, match situation, area of pitch.
    • Data aggregated to player-within-match, player, team and match levels.
    • Background data collected on players, teams, matches.
  • Results
  • Using our adapted Loland classification of cheating
    • In total, 390 incidents of cheating (an average of 5.96 per 90 minute match; 70% detected and punished by referee in some way).
    • 97 incidents of Classic Cheating (1.48, 11% detected), which included 83 incidents of simulation (1.27, 12% detected).
    • 293 Professional Fouls (4.48, 87% detected).
  • Results
  • Cheating rates per 90 minutes by type: ‘top’ 3 players, matches, teams:
  • Rogues
  • Gallery:
  • Professional Fouls
  • Classic Cheating
  • Players:
  • S. Papastathopoulos (Greece) 2.14
  • B. Emerton (Australia) 1.42
  • J. Carragher (England) 1.34
  • K. Keita (Ivory Coast) 1.91
  • C. Blanco (Mexico) 1.61
  • C. Ronaldo (Portugal 1.50
  • Matches:
  • Portugal vs Brazil (Grp R3) 14.00
  • Slovakia vs Italy (Grp R3) 10.00
  • Denmark vs Japan (Grp R3) 10.00
  • Slovakia vs Italy (Grp R3) 8.00
  • Chile vs Switzerland (Grp R2) 7.00
  • Ivory Coast vs Brazil (Grp R2) 6.00
  • Teams:
  • Australia 4.33
  • Cameroon 3.67
  • Brazil 3.50
  • Italy 2.00
  • Portugal 2.00
  • Chile 2.00
  • Results
  • Cheating rates per 90 minutes by type, team:
    • Professional fouls
    • Classic Cheating
  • Results
  • Predicting propensity for committing professional fouls:
    • Aim to assess extent of and explain any variation in professional fouling at player, team, opposition and match levels.
    • Data analysed at player within match level.
    • N = 1763 appearances by 599 players from 32 teams, over 64 matches.
    • Distn of DV: 0 = 85%, 1 = 13%, 2 = 1.5%, 3 = 0.5% Count data of rare events; modelled as Poisson, slightly under-dispersed (dispersion parameter = 0.8).
    • Offset term – playing time in that match.
  • Results
  • Predicting propensity for committing professional fouls:
    • Cross-classified multilevel data; incidents nested within players and matches, players nested with teams, matches defined by the cross of team and opposition.
    • Models fitted using generalized linear mixed models using the lmer function from the lme4 package in R.
    • Unconditional model fitted first to estimate variance partition coefficients via exact calculation formulae of Stryhn et. al (2006)
    • Predictors added; match or team level predictors assessed one-by-one due to small samples.
  • Results
  • Predicting propensity for committing professional fouls:
    • In unconditional model (Deviance = 1094), higher level VPCs given playing time of 90 minutes:
      • Player = 7%,
      • Match = 3%,
      • Team and Opposition < 1%.
    • Variance largely due to between-player differences within matches.
  • Results
  • Predicting propensity for classic cheating:
    • Numbers of events per player per match very low (95% = 0), hence data aggregated to player level i.e. DV is number of simulations carried out by each player over tournament.
    • 97 offences in total across 599 players from 32 teams.
    • Distn of DV: 0 offences = 88%, 1 = 8%, 2+ = 4%.
    • Offset term – player’s total playing time in tournament. Also controlled for minutes team played to attempt to proxy importance of matches faced.
    • DV is count data of rare events; modelled as Poisson, though slightly over-dispersed (disp parameter = 1.1).
  • Results
  • Predicting propensity for classic cheating:
    • In unconditional model (Deviance = 353), estimated higher level VPC at total playing time of 360 minutes:
      • Team = 11%.
    • Variance largely between players within teams. Team effect is small but not trivial.
  • Results
  • Predicting propensity for classic cheating:
  • Random effects plots:
  • Model with player position and national culture
  • Results
  • Predicting propensity for classic cheating:
  • Classic Cheating vs National Cultural Dimensions:
  • Power Distance
  • Uncertainty Avoidance
  • Conclusions
  • Predictors of professional fouling:
    • Playing position in match: GKs, Forwards, Wingers less likely to commit professional fouls than centre-backs / central midfielders. Opportunity/situational effect.
    • Caps: experienced international players less likely to commit professional fouls. Experience may mean better positioning hence less need top foul; greater ability leads to more caps, less need to foul.
    • Importance of match to team: frequency of offences increases when result of match has immediate importance to team.
  • Conclusions
  • Predictors of classic cheating:
    • Typical Playing position: Forward midfielders/’free-role’ most likely to commit classic cheating. Opportunity/situational effect.
    • National cultural dimensions: Nations with high power distance and high uncertainty avoidance - such nations are typically located in Latin America, Latin Europe, Eastern Europe - are most likely to commit classic cheating.
    • National cultural dimensions effect matches that found by Franke & Nadler (2008) in a business ethics scenario.
  • References
  • Cashmore, E. (2000). Sports culture: An A to Z guide.
  • D'Agostino, F. (1981). The Ethos of Games, in W.J. Morgan and K. Meier (eds). Philosophic Inquiry in Sport.
  • Franke, G. R. & Nadler S. S. (2008). Culture, economic development and national ethical attitudes. Journal of Business Research.
  • Hofstede, G. (1980) Culture's Consequences: International Differences in Work Related Values.
  • Loland, S. and McNamee, M. (2000). Fair Play and the Ethos of Sports: An Eclectic Theoretical Framework. Journal of the Philosophy of Sport.
  • Loland, S. (2005). The varieties of cheating — comments on ethical analyses in sport [1]. Sport in Society.
  • Nicholls, J. G. (1984). Achievement motivation: Conceptions of ability, subjective experience, task choice and performance. Psychological Review.
  • Nilsson, P (1993). Fotbollen och moralen. En studie av fyra allsvenska fotbollsföreningar.
  • Rest, J. (1984). The major components of morality. In W. Kurtines & J. Gewirtz (Eds.), Morality, moral behavior, and moral development.
  • Ronen, S. & Shenkar, O. (1985). Clustering Countries on Attitudinal Dimensions: A Review and Synthesis Academy of Management Review.
  • Schein, E. H. (2005). Organizational Culture and Leadership.
  • Searle, J. (1969). Speech Acts: An essay in the philosophy of language.
  • Shields, D., & Bredemeier, B. (2001). Moral development and behavior in sport. In R. Singer, H. Hausenblas, & C. Janelle (Eds.), Handbook of sport psychology (2nd Ed.).
  • Stephens, D. (2000). Predictors of Likelihood to Aggress in Youth Soccer: An Examination of Co-ed and All-Girls Teams Journal of Sport Behaviour.
  • Stryhn H., Sanchez J., Morley P., Booker C. and Dohoo I.R. (2006) Interpretation of variance parameters in multilevel Poisson regression models
  • Wilson, J. (2007). Behind the Curtain: Travels in Football in Eastern Europe
  • Contact
  • c.b.stride@sheffield.ac.uk


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