Transcript Team culture, player behavior, or question of circumstance?

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 incidents by type, playing position of offender:
Results
Cheating rates per 90 minutes by type: ‘top’ 3 players,
matches, teams:
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
Rogues
Gallery:
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
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 centrebacks / 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/’freerole’ 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
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Contact
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