1. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 The Effect of Incentives on Sabotage: The Case of Spanish Football Julio del Corral Juan Prieto-Rodríguez Rob Simmons

2. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 1.Introduction 2.Data 3.Empirical model 4.Results 5.Conclusions

3. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 Lazear (1989) developed a theoretical model where agents may respond to increased incentives by taking actions that reduce rival's output –A key pre-condition for this result is that rewards depend solely on relative performance Sports leagues are useful settings in which to analyze changes in behaviour following changes in rules –Rewards in sports matches are relative: if one team wins, the other loses- as required by Lazear’s theory of sabotage

4. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 In sports economics is becoming more common to study the consequences of rule changes: –Ice hockey: Allen (2002), Levitt (2002) and Heckelman and Yates (2003) studied the effects of adding an extra referee. It appears that increasing the number of referees did not induce players to commit fewer fouls –Ice hockey: Abrevaya (2004) study the effects of the new points regime in the NHL and found that, although the incidence of tied games fell, the proportion of games going into overtime rose as an unintended effect of the change in incentives –English football: Witt (2005) finds that the number of expulsions did not increase following a rule change (tackle from behind). However, the numbers of cautions for less severe infractions rose, suggesting that players substituted one type of illegal activity for another

5. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 The focus of this paper is the radical change in points incentive introduced in English football in 1981 and, installed in 1995 in other European Football Leagues –The winning team received two points before the rule change while three points are earned after the reform The purpose of this reform was to encourage more attacking football –However, there are some papers which have not found this result either theoretically (Brocas and Carrillo, 2004) or empirically (Correira and Machado, 2002; Palacios-Huerta, 2004). The unexpected and undesirable effect was an increase in defensive effort offsetting any increase in attacking effort

6. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 An increase in defensive effort could follow a change in points per win partly because –The cost of going behind in a game is increased –but also because teams that go one goal ahead may be more inclined to protect their lead rather than increase it Our hypothesis states that if teams face an increased relative value of winning, they will be more prone to commit sabotage –We predict that a rise in defensive effort will spill over to some extent into illegal activity and that, in turn, the likelihood of a team receiving at least one dismissal is raised

7. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 Garicano and Palacios-Huerta (2006) studied the consequence in yellow cards and offensive efforts of the three points rule in the Spanish Football League In contrast, we analyze the effect on red cards which have a larger impact –Any significant increase in the red card number should be related with a rise of the expected benefits of those actions that raise the probability of being punished As long as our data set capture an adequate natural experiment that keeping other thing unchanged but the relative incentives of a match victory, we are confident that the change in the average number of red cards per match is related with changes in the incentives, achieving new evidence in favor of Lazear’s hypothesis.

8. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 Our data comes mainly from the referee's official pot- match reports (www.lfp.es) –Team's budget and attendance is taken from Garcia and Rodriguez (2002) Data correspond to 1994/95 and 1995/96 seasons of the Spanish First Division –This comprises 20 teams in 1994-95 and 22 in 1995-96 To use adjacent seasons has some advantages: –Similar teams (apart from promotion and relegation) and similar players appear in each season –We expect behaviour to adjust quickly as successful strategies to deal with the new incentives would be quickly imitated –The two selected seasons did not have any other rules changes and hence the points change is the major change in incentives

9. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 It can be seen that the worse the state of the match the larger number of red cards in each season Teams which are behind in score generate extra effort on scoring and some of this extra effort will translate into illegal activity The number of sending-offs per match in the 1995-1996 season increased significantly from the 1994-1995 season This change was not the same for the three feasible game states

10. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 The increasing probability of red card over time seems reasonable: Majority of red cards are due to double yellow cards (56% in our sample) Referees can be more reluctant to expel players in the beginning of the match since this decision could have a larger impact on the match result [see Ridder et al. (1994), Torgler (2004), Caliendo and Radic (2006)]

11. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 We estimate probit models with appropriate control variables –Our unit observation is the period of time in which the state of the match (win, draw, loss) remains unchanged For each period of time in which the results remains unchanged there are two observations (i.e., one for the local team and one for the away team) In this way, there 4,258 observations from 842 matches

12. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 The dependent variable takes the value of one whether there is at least a sending-off for the team considered and zero otherwise Independent variables are: –Pre-game control variables for team and game characteristics Log difference of budget interacted with the dummies for the seasons (LDIFBUDGET94, LDIFBUDGET95) Dummy for derby matches (DERBY) Match attendance (ATTENDANCE) Dummy variable for the home team (HOME) –Time of observation: Length of each observation in minutes and square (TIME, TIME2) The minute in which begin the observation (PBEGIN) A dummy variable which takes value one if the observation belongs to the beginning of the match (DMBEGIN) and another if the observation belongs to the ending of the match (DMEND) –Within-game controls for state of the match A dummy variable if the team is winning (WIN) and another one if the team is losing (LOSS)

13. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 We include the variables LOSS, DRAW and WIN interacted with a dummy that takes value of one for the season 1995-1996 –These variables reflect the difference in the behaviour of teams between the two seasons for each feasible result –We expect that the sign of D9596WIN would be positive since the winning teams are more encouraged to defend the result in the 1995-1996 season than in the previous one –In order to control for the existence of an overall season effect regardless of the result we also estimate an alternative model including only a dummy variable for the season 1995-1996

14. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 Estimated coefficients and marginal effects Notes: (a) ***, **, and * denotes statistical significance at the 1%, 5%, and 10% levels, respectively. (b) Models include team individual effects and referee individual effects.

15. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 Coefficient on the D9596WIN is positive and significant –Hence, in 1995-96, winning teams commit more offenses that are punishable by red card Coefficient of D9596LOSS is negative and significant –This could reflect the decrease in the incentives for a draw Coefficient of D9596 is not significantly –Hence, this result is hidden an opposite effect for wining and losing teams that compensate each other Coefficient on D9596END is positive the likelihood of a red card at end of game is higher in the 1995-1996 season –higher relative incentives for each victory combined with a decreasing expected cost of punishable actions (as the end of the match approaches) leads to a significant rise in red cards

16. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 The negative coefficients of LDIFBUDGET94 and LDIFBUDGET95 are statistically significant –We do not reject the null hypothesis that the difference is zero DERBY matches have higher probability of sending-offs The negative coefficient of HOME could reflect a less severe attitude by the referees toward local teams –Positive discrimination All the timing variables have the expected coefficients –TIME has a positive coefficient and TIME2 a negative one the larger the period of the observation the higher the probability that a sending-off takes place but with a decreasing marginal effect –DMEND has a positive coefficient in the last minutes there is a greater likelihood of a sending-off

17. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 Lazear (1989) proposed that if rewards were dependent solely on relative performance then an increase in rewards would induce agents to engage in activity to reduce rivals’ output. –We have tested this hypothesis using the natural experiment of a rule change in Spanish football, the increase in points for winning a league match from two to three. Our results are consistent with Lazear’s hypothesis: –First, teams in a winning position were more likely to commit offences punishable by dismissal of a player in the three points reward than in the two points –Second, there is a higher probability of red cards in 1995-96 season as the end of the match approaches regardless the winning position of the team

18. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 There were no other changes in rules of football over the time period that we investigate and also no reason to expect a change in application of the rules by referees –Monitoring and detection activity can be regarded as constant –We have controlled for pre-game and within-game influences on likelihood of dismissal –Given the lack of other external conditions surrounding player dismissals and given the presence of an appropriate set of control variables, we consider our results to be supportive of increased sabotage behaviour following the increase in rewards for winning

19. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 We find that increased rewards for winning spills over into increased illegal activity, as observed and punished by football referees Actual punishment for actions deserving a red card consist in players dismissals and this may make the contest more unequal and less interesting as the team with reduced personnel operates a more defensive style of play. A different system of punishment to these sabotage actions could help to prevent or reduce them. –For instance, rather than dismiss players a red card could be punished with a penalty kick in spite of where the action has taken place

20. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008 THANKS FOR YOUR ATTENTION!!!

21. IntroductionDataModelResultsConclusions IASE Annual conference. Gijón May 9-10, 2008