Mourinho & Benitez

Coach Dismissal Influence on In-game Performance

The elite European football clubs always try to select the best available coach in order to meet their goals. These selections are not always the best and some coaches are getting fired, before the season ends. In these situations the clubs have to pay large compensation fees after a coach’s dismissal to provide the players fresh motives.

The research is conducted to validate if the coach’s dismissal affect the in-game performances of the team.

  • The examined sample includes the clubs that have finished 1st, 2nd, 3rd or 4th in the previous season’s national championships in Europe.
  • The data collected from Belgian, English, Italian, Spanish, Portuguese, Greek, German and Dutch soccer championships.
  • The starting year of a possible dismissal selected to be 2000 and the last observation is Anceloti who sacked from Bayern München in 2017.
  • In order to be included in the sample the team should have played at least 10 matches before the dismissal and 5 after to observe the instant reaction of the team. 

To begin with, it is important to indicate some characteristics of the data. For instance, the total time that a coach was in the bench seems to differ between countries of North and South Europe. The average for North countries is 21.88 months in the bench and for the South is 14.07 months. Nevertheless, (Ho: means are equal) the Two-tailed T-test assuming unequal variances method proves that the difference between the two means is not statistically significant (p-value=0.101755, confident level: 95%). According to this outcome, there is not difference between Mediterranean spontaneous managers and more cool-headed Nort European.

Before 2010 the average employment for a coach was 19.1 months and after 2010 the average has been dropped to 15.75 months. Taking into consideration the null hypothesis (Ho: means are equal), the Two-tailed T-test assuming unequal variances shows that the difference between the two means is not statistically significant (p-value=0.480188, confident level: 95%). Through the years there is not any change on how club managers could act if the team does not perform well.

It is clear that managers select the winter months to sack their coaches. It is the period when the team has shown what it is capable of and there is also time to turn things around and improve the team’s performance. More than ¾ of dismissals happened in winter months(77%), only 5% in September, 9% in November and 9% in March.

The most important question to answer in this research is the following: Are the results getting improved after the coach leave? The average number of points in 10 matches (1,68) before the exit of the coach will be compared with the average points in the 5 matches after the coach’s exit (2,2). The following graphs illustrate these two periods and the percentage of the improvement from the 10 matches to 5 matches. Null hypothesis in the current case is the average of 10 matches to be equal to 5 matches average. Two-tailed T-test assuming unequal variances method proves that the difference between the two means is statistically significant, as the confidence level is defined in 95% and the p-value is 0.003698. So it is right to believe that a coach’s dismissal in the middle of a season, returns better results, instantly.

A very interesting result that can be extract from the historic data includes the comparison of the last result before dismissal compared to the first result after that. The comparison could be observed from the graphs above. The percentage of wins in the last game happens to be equal to percentage of losses in the first match.

Regarding the goals a team scored in these 10 matches (1.77), comparing with the 5 matches (1.87), it should be mentioned that elite teams usually score more than 1.5 goals per match to secure the win and the high table place. The Two-tailed T-test assuming unequal variances method (Ho: two means are equal) shows that there is not statistically significant difference between these two means (p-value=0.637757 and confident level 95%). As a result, the offense of the above clubs was not the main problem of the teams’ performances.

On the other hand, the opponents’ scored goals is a factor that change after the dismissal of the coach. The mean of 10 games is 1.2, while the mean of the next 5 games is 0.82. Practicing the Two-tailed T-test assuming anequal variances method (Ho: two means are equal) validates the assumption that defense had better results after the last 10 games. With confident level 95% and p-value 0.005828, the difference of these two means is statistically significant. When a coach leaves a club, the team’s defense get better instantly.

The last observation relates to the goal difference per game, in the last 10 games of the coach and in the 5 next games. For example if a the result of a game is 3-1 win, the absolute goal difference is +2.

To conclude with, the researcher validated above that a coach’s dismissal affexcts the in-game performance significantly. Elite European football clubs are not used to failure and their managers are almost obliged to succeed. Some of the dismissals are the result of a sequence of bad relations between coaches and players or owners, but it is generally acceptable that most times, if the team wins, the manager is safe.

Every second of the day I am surrounded by numbers. My academic background in Statistics, helped me acquiring knowledge to collect and process data effectively. My ambitions are to conduct researches that only a few people think and most people are willing to read. Statathlon is a different project with professional analysts and intriguing researches with unique outcomes.

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