How Fouls Impact Game Dynamics in the Football World Cup
Friday's match between Brazil and Colombia brought into focus how devastating fouls can be in the World Cup. Though Brazil won the game 2-1, its star player Neymar suffered a lumbar vertebra fracture when he was kneed in the back by Colombian defender Juan Camilo Zuniga. Zuniga was called for a foul.
The World Cup has a long history of (in)famous fouls that some may claim changed the outcomes of the games. Zidane's head butt in 2006 definitely comes up top on that list.
Curious about the dynamics of fouls, I decided to look into the history of fouls in the World Cup. I downloaded data from all the World Cup games from 1930-2010 from the FIFA website. After normalizing the data to account for the difference in matches played, I generated a heat matrix of correlations between various game play metrics using PatternEQ's correlation analysis tool (sign up for a beta trial here).
An interesting insight from this data, is that there's an extremely strong correlation (0.91) between fouls committed (FC) and fouls suffered (FS). This seems to imply that teams respond to fouls with fouls of their own. Case in point: in Friday's game, Brazil committed 31 fouls and Columbia committed 23.
There's also a strong correlation between fouls committed/suffered and yellow cards (Y) received (0.58).However, there's no correlation between fouls committed/suffered and red cards handed out. This is interesting because I expected that as the game play becomes more heated and aggressive, the probability of a red card being handed out increases. But the data doesn't suggest so (Correlation strength of only 0.01).
But do fouls help teams win. The answer is, not really. Teams that commit fouls are also likely (correlation strength of 0.78) to hit a lot more shots on goal (SOG). However, there's a slightly negative correlation (-0.16) between goals scored (GF) and fouls committed. Looks like playing dirty doesn't really pay off.
Overall, in this year's World Cup, Brazil leads with the most number of fouls committed so far with an average per match of 19.2. As the above correlation suggests, Brazil also suffered an unusually high number of fouls with a count of 95. It's an eye for an eye!
Note: If you wish to run a similar analysis yourself, sign up for the beta trial of PatternEQ here.
Data Engineering and Analytics Manager
6 年Football+Data. My favorite couple. Thanks for not calling it soccer btw.
Owner/Attorney
10 年Uzma, since correlation does not equal causation, then we can't say that the correlation between FC and FS is the result of teams responding to fouls by fouling back. This would imply causation, no? I'd be interested to see if we could find other non football factors here such as GDP differential between the countries playing the match.
Business Developement Manager at Cognizant
10 年One reason that there's no correlation between fouls committed/suffered and red cards handed is that players take turns in getting yellow cards.. A player without a yellow card becomes the agressor & player with a yellow card becomes more passive & cautious while tackling limiting the probability of a red card
Ashwin, this analysis doesn't imply that not fouling helps the team win. Fouling doesn't specifically help you win, there's no correlation between fouling and goals scored. To analyze if not fouling helps one will have to separate out teams that committed fewer fouls and analyze their record against teams that committed more. Moreover, outliers can always exist. Remember, correlation is not causation.
So according to this, if Brazil keep on fouling Germany tomorrow, and Germany don't reciprocate, then Germany wins?