Legendary German goalkeeper Manuel Neuer once said: “You can plan, but what happens on a football pitch cannot be predicted. “
This sentiment largely explains why soccer is the most popular sport in the world. Anything can happen on the pitch, and the more surprising the outcome of a match, the more memorable it will be.
But our new study suggests that the results of football matches are becoming more and more predictable.
We have developed a computer model to predict football match results based on the data of almost 88,000 matches played over 26 years (1993-2019) in 11 major European leagues. Our model tried to predict whether the home or away team would win by looking at their performance in a number of previous matches.
Our model is simpler than the advanced predictive models used by betting houses today. It requires very little data and is easy to set up and train, which has the advantage of being able to go back, say, 20 years or more. The data available on matches played 20 years ago would not necessarily be detailed enough to fuel more sophisticated models.
Its simplicity means that our model will be less accurate than more complex predictive models. Despite this, our model correctly predicted results about 75% of the time.
A widening gap
We have found that it has become easier and easier to predict the results of soccer games over the years. For example, our model was able to correctly predict the winner of a Bundesliga (German League) match in 60% of matches in 1993, while his performance reached 80% in 2019. It is not because we now have more data on which to base our predictions – although we do, we always trained the model with the same amount of data.
We were surprised at first that the results of football have become more predictable. We thought more money and higher stakes must have made the game more competitive over time, so we should expect more excitement and less predictability in recent years. A closer look at the data helps us understand why this is not the case.
When we looked at teams from the same league in a given season, we observed that over the past few years the points have been distributed among the teams much less evenly. We quantified this disparity by calculating the Gini coefficient (traditionally used in economics to measure inequalities in wealth and income) of the points distributed among the teams at the end of each season.
This allowed us to measure the point difference between the strongest and weakest teams. We have observed that over the past 26 years, the gap has widened: the Gini coefficient has increased by around 70%, from 0.12 to 0.20 in the big league. Essentially, this means that overall, stronger teams are more successful, while weaker teams are less successful.
This echoes the idea that “the rich get richer and the poor get poorer”. This widening gap could be the result of a cycle where the stronger teams end up making more money, making them even more powerful in the player market, which then leads to an even stronger team.
Another trend in our results helped us understand why football matches might become more predictable. As football fans know, many of the most exciting games take place when a strong team is playing on the field of a weaker team, and the weaker home team, relying on support often. epic of his fans, ends up winning.
We calculated “home advantage” as the ratio of the points the home teams collect to the points the away teams collect on average. Remember that each team faces each other twice in a season: once on each team’s field. This symmetry allows us to measure the pure effect of home advantage.
We saw an initial 30% advantage on the pitch in the early 90s, meaning that on average a home team was 30% more likely to win (65% of the time vs. 35% of the time) per compared to a team playing far. The home advantage has gradually narrowed to just 15% in recent seasons. In other words, it has halved over the past two and a half decades.
There are therefore less and less chances for the weaker teams to benefit from playing at home. It seems, in general, that the stronger teams will win anyway, no matter where they play.
This could be in part because transportation and training have improved dramatically over the past few years, minimizing the logistical challenges of playing away from home and making it easier for players to adapt. But more importantly, it seems like further proof of the growing strength of the stronger teams.
So what can we do?
There are some limitations to our study. We only looked at the top 11 European men’s leagues and our analysis does not go back further than 1993. Also, for technical reasons, we did not include ties in our analysis. If you’re wondering, the number of links has also gone down, which is consistent with our other observations.
Nonetheless, the results of our work are strong, especially for bigger leagues such as England, Spain and Germany.
Our results underscore the need for stricter regulations around club income, spending and player salaries, including, perhaps, the introduction of more effective caps. Otherwise, the success of the sport could become the very reason for its decline. A game that is easy to predict is not a game that will necessarily draw crowds to the stadiums. – The conversation