Posted on February 12th, 2019
“The rich get richer and the poor get poorer”. This particular adage by Percy Shelley is most often used to describe the economic inequality caused by free market capitalism. However, it is strangely appropriate to describe what is happening to team performance in leagues in Europe. The strong are getting stronger as the weak are getting weaker.
In the 2000s, an apparent gap in team strength between the top 4 Premier League teams and the rest led people to start using the term the “the top 4” to refer to the teams that people considered consistently and clearly ahead of the rest in terms of performance. Just last summer, we saw Man City win the Premier League with a record breaking 100 points, indicating that there is likely a widening the gap in team quality in the Premier League. This is better illustrated in the animation below, which shows the distribution of points in the Premier League from 1995 onwards (when the format changed to a 20-team competition).
The existence of this phenomenon shouldn’t come as a complete surprise since good teams that perform well end up getting more money from commercial and sponsorship deals, matchday revenue, etc. as well as build up a history and reputation of success. These then allow them to recruit better players and staff and this positive feedback loop results in widening of the gap in team strength in the league. This isn’t something restricted to the Premier League either. In fact, we expect it to happen to a greater extent in some other leagues since some allow teams to negotiate their own televised matches deals independently (e.g. Spain) rather than having the televised matches deals negotiated centrally and the revenues distributed evenly across teams as occurs in the Premier League
We wanted to measure this effect in a more rigorous manner to quantify the change in team strength inequality, and to see how it compares across leagues. To do this, we can look at the distribution of points in the league table over time. More specifically, we are looking for inequality in the points distribution. Fortunately, there’s a well-established measure used in economics called the GINI coefficient that helps us to do this. It is commonly used to measure income inequality or wealth inequality, but we can use the underlying concepts behind the GINI coefficient to measure points inequality in leagues and track changes over time.
The way the GINI inequality measure works is… for any given season, starting with the weakest team (bottom of the league table), we measure the share of league points that the team accounts for and gradually include more teams until we consider all 20 teams in the league (at which point these will account for a 100% share of the points accumulated in the league). When these values are plotted, it creates a curve whose gradient characteristics encode the distribution of points in the league. In the case of a perfectly equal league where all teams get the same number of points, this graph will look like the line of equality (perfect triangle). Any deviations from this are a sign of inequality in the league, and the extent of the equality (or inequality) can be measured by the area under the curve relative to the hypothetical perfect equality case. The distribution of points in the Premier League and the corresponding GINI curve are shown below for reference.
The results below show how the league inequality has changed for the top 5 leagues in Europe since each of them changed format to their current league structure (18 teams for Bundesliga and 20 teams for the rest).
On average, across the past 10 years, Ligue 1 has been the most evenly matched league from the top 5 in Europe, followed by the Bundesliga. La Liga, Premier League and Serie A all have greater disparities in team strength in the league and are roughly similar to each other in that respect. A similar pattern is observed even if we just look at the inequality in league points last season. The Bundesliga had the most even distribution of league points, followed by Ligue 1, then La Liga, Premier League and Serie A.
Key results are summarised in the table below:
||2017-18 season inequality (level of disparity in points between teams)
||Average inequality over last 10 seasons
||Inequality trend (change in inequality coefficient per year)
Crucially, all 5 leagues exhibit a trend of increasing points inequality over time, and it is statistically significant increase in all 5 cases (p<0.01). The inequality in team strength is increasing most rapidly in the Serie A, followed by La Liga, while the Premier League, Bundesliga and Ligue 1 appear to be the comparatively protected from the team strength positive feedback phenomenon.
This may be a slight problem for the future of football, since the sport may lose some appeal if the league positions become increasingly predictable over time. We wouldn’t be surprised if more rules were put in place to limit team spending in the near future to try reel this problem in, particularly in Italy.
We should enjoy this season’s competitive title race between Man City and Liverpool while it lasts. Leagues are likely to get increasingly less competitive over time.
Posted on December 3rd, 2018
What happens to teams when they get relegated? How much do their squads end up changing as a result of relegation, and how does it impact on-pitch performance?
We have performed some analysis on the last five completed PL and Championship seasons (i.e. 13/14 to 17/18) to try to answer these questions.
We first investigate the minutes played by players that start in a team’s squad, and look at how those minutes change in the following seasons – but only minutes at the same team are counted. We do this to get at how changes in squads practically affect the actual players fielded. Specifically we measure the overlap in minutes played across the team from the starting season. If a team uses the exact same mixture of players in its matches we would observe a 100% similarity/overlap, whereas if a team has replaced all its players we would see a 0% similarity/overlap. The chart below shows the monthly evolution of these overlaps, averaged for teams that remained in the PL, teams that were promoted to the PL, teams that were relegated to the Championship and teams that were already in the second tier league.
We see that relegated teams, more than the other categories, tend to use on average only about 40% of the previous season’s squad in the new season. Teams participating in the PL tend to have a more similar set of players, starting at around 60% and declining with time. This is not a surprising observation. Relegated teams face a financial challenge, with considerably reduced revenues despite parachute payments. At the same time, many players will not want to compete in the Championship after being in the PL. What is interesting here is the difference between the PL and Championship for teams that were already there. Teams in the PL have more stability in their fielded players.
The graph above shows us that PL teams lose more players when they get relegated. But are the players they lose key first team players or mainly reserve players? To find out, we can look at the minutes played (as a proportion of possible minutes played) over the course of the season by players who eventually leave at the end of the season. To get a good understanding of what’s happening, we can do the same for players that end up leaving the subsequent season too.
This graph reveals that not only do teams that get relegated from the PL lose more players than if they stayed in the PL or teams already in the Championship, but it also shows that the players that leave tend to be key first team players that played a fair amount of the season. These changes come as a result of an average 10 new players for the relegated teams, versus 11 for teams already in the Championship. For both sets of teams, the percentage of new players coming from a team that participated in the previous season’s Championship is similar, at around 25%.
We now turn to review the net spending of relegated teams, compared to teams already in the Championship. On average the relegated teams have bought around £23M worth of players in the season after relegation compared to only £7M by teams already in the second tier league. On being relegated, not surprisingly, relegated teams sold on average about £29M worth of players, which makes a negative average net spending of -£6M. Regarding net spending of the existing Championship teams, the average was around zero, i.e. they were spending as much buying as they were getting from selling players. This highlights the degree of the financial challenge relegated PL teams face.
Turning now to performance: Relegated teams have a 1 in 3 chance of being promoted straight back into the PL. According to our league table simulations this proportion was expected to be 27%, so the newly relegated teams seem to slightly over-perform in that sense. If we instead compare their finishing position in that first season to what we’d expect of them, then they actually under-perform: the average relegated team’s expected position in their first Championship season was 6th, the observed was only 9th. This is an interesting apparent contradiction. It suggests that while many teams do well, others do very badly – thereby dragging the average league position down.
In terms of team strength, according to our team strength model, the overall strength of newly relegated teams tends to decline after a season by an average of 4.3%, compared to the teams’ strengths at the time of relegation. This is a relatively modest change against the backdrop of such large changes in playing staff. It should be noted however that for a team to be relegated in the first place their strength cannot have been especially impressive to start with.
In general we think the main message of the above analysis is that there seems to be an indisputable decline in strength after relegation to the Championship for a typical team. But at the same time there is a larger than expected number of teams that make it straight back to the PL and the actual team strength decline does not appear to be especially severe. For the team itself the question of interest is whether they will be one of the third that makes it straight back and, if not, will they be one of the teams that drags down the average?
We attempted to answer this question by looking for correlations between the relegated teams and their subsequent performance. We found that teams with higher spends managed to temper the team strength decline the most. So, money does help. We also found that teams that are able to keep more of their playing staff tend to finish in higher positions. These findings are of course related. The message is that keeping your squad as close to intact as possible is what the evidence suggests is the best move.
Posted on September 17th, 2018
The group stages of the Champions League is set to kick-off tomorrow.
A summary of our Champions League forecasts is shown below. The team most likely to win the competition is Barcelona (20.3%), with Bayern Munich (18.4%) and Real Madrid (16.1%) being the next most likely teams to win the competition.
Looking at the progression chances split by each group shows that all groups have at least one clear progression favourite, with >80% chance of progression to the round of 16. The fight for the second progression spot is toughest in Group E, where Benfica, AEK and Ajax are closely matched. Group F is also relatively competitive. Porto got very lucky with the group stage draw since they’re very likely to progress to the round of 16 (80.9% chance) despite only being in the bottom half of teams in terms of team strength. Napoli, on the other hand, got the short end of the stick since they’re the 15th best team in the competition but only have a 29.8% chance of going through to the round of 16.
Finally, forecasts for individual matches can be found below. Real Madrid vs Victoria Plzen is the most one-sided fixture in the group stage. From the big teams in the tournament, the Liverpool vs PSG fixtures are the most evenly matched.
It will be interesting to see how far Man City and Liverpool can carry the banner of English football on the European stage.
Posted on July 16th, 2018
The world cup is over. It’s been a thrilling month of exciting matches, great goals and surprises. Events like the world cup get discussed and mentioned a lot on Twitter. This allows us to determine which events sparked the most discussion, as well as establish which teams got the most positive response from the Twitterverse.
Let’s start by taking a look at the top moments of the World Cup. We measure this by looking at the moments that led to the most discussion on Twitter, so many will be heavily context dependent rather than noteworthy standalone moments. The top moments as far as the Twitter community was concerned were England getting knocked out of the World Cup, Cristiano Ronaldo’s hat trick against Spain and England finally winning a match on Penalties. Other key moments are shown below.
We can also use sentiment analysis to find out which teams impressed people the most and which teams people were less pleased with.
France, Belgium and England lead the way for teams that people responded the most positively to. Croatia were 7th in comparison. The teams that people responded most negatively to were Saudi Arabia, Colombia, Argentina, Egypt, Poland and Germany. Spain and Portugal also received relatively poor responses overall.
There’s not much left to say on the World Cup, except congratulations to France! Not only did they win the world cup, but they did so in a manner that impressed the Twitterverse!
Posted on July 12th, 2018
The World Cup semi-finals are over. France and Croatia have progressed to the finals of this year’s World Cup.
Below are our predictions for the World Cup final and third place play-offs:
Posted on July 11th, 2018
The 2018 World Cup is drawing to a close. It’s been a very interesting and dramatic tournament to follow.
There has been a lot of discussion on how this World Cup stands out in terms of the nature of the goals scored. In particular, there is a lot of discussion around the increased number of penalty goals, own goals and late goals in the game. This begs the question: Are there really more of these types of goals and how do the own goal, penalty and late goal rate compared to the Premier League?
The graph below shows the distribution of goal times in a game. This World Cup, 14.3% of all goals scored were scored after the 90th minute! To provide some context, in the Premier League, only 5.1% of all goals are scored after the 90th minute.
The table below compares the goal rate this World Cup as well as the number and proportion of penalties, own goals and late goals.
The overall number of goals per match this World Cup is slightly lower than the 2014 World Cup, and around 10% lower that the average number of goals in a Premier League match. The distribution of types of goals is quite different to the Premier League, however. 16% of all goals this World Cup have been penalties (compared to the 6.8% observed in the Premier League), 20.5% of all goals have been own goals (compared to the 3.5% seen in the Premier League) and as stated earlier, there are 2.8 times as many goals scored after the 90th minute as we observe in the Premier League.
Several people have also commented on the number of apparent surprising results. For example, Germany getting knocked out of the Group Stage, Russia beating Spain, Belgium beating Brazil, etc. Has this World Cup really had more surprising results than previous ones? The graph below compares how unpredictable the results of the competition have been.
The number of unexpected results in this World Cup has been in line with the levels observed in previous World Cups, but more surprising than the Premier League. The World Cup with the most surprising results in the recent past is 2010 and the World Cup with the least surprising results has been in 2006.
It looks like this really is a World Cup of late goals, own goals and penalties, but the number of own goals is particularly remarkable. It wouldn’t surprise us if England – Croatia match tonight ends up being won by a 90th+ minute own goal or penalty!
Posted on June 28th, 2018
England are going into their third and final match against Belgium this evening as favourites to with the match (38% chance of winning), but should they win it?
There has been much discussion in the past couple of days on the potential benefits of England finishing second in group G to have an easier run of fixtures in the knock-out stages of the competition.
If England finish second in the group, they have a 7.7% chance of winning the World Cup compared to only a 6.2% chance if they finish first (the calculations were run before the last set of group H fixtures were played, so the teams that finished first and second in group H are not known at the time of writing). This is largely due to the likely event of having to face Brazil in the Quarter finals if they progress to the round of 16 as top of group G rather than Sweden or Switzerland if they finish second in the group.
The full list of likely opponents for each stage of the competition can be found below.
Regardless of the result tonight, England fans can take comfort in knowing that they are guaranteed to go through to the round of 16. It will be interesting to see if they choose to do that by giving it all they’ve got or prefer to game the system and maximise their chances of winning the world cup.
Posted on June 25th, 2018
England’s second game against Panama played out considerably better than their opening game against Tunisia. The graphs below show how Twitter responded during the course of the match.
Social media activity was at its highest just after Harry Kane scored his second penalty to make the score 5-0 shortly before half time, but the most positive comments came just after the Jesse Lingard long range goal.
Despite the response to Harry Kane’s second penalty goal against Panama being the strongest response that match, it still doesn’t match the response to his late winner against Tunisia.
The Panama match as a whole is now the most talked about match on Twitter, followed closely by the Argentina vs Croatia match.
Other key moments in the world cup that elicited strong responses on Twitter are Argentina’s 3-0 loss to Croatia and Toni Kroos’ spectacular 95th minute goal against Sweden to win the match.
Posted on June 25th, 2018
With the World Cup firmly underway, each team only has one match left to play in the group stage.
Brazil and Germany have the greatest likelihood of winning their respective 3rd round matches, each with a 73% chance whilst Croatia, Argentina, Spain and Colombia also have a reasonably high chance of victory. Japan’s game against Poland may prove to be the most entertaining with an average of 3.1 goals scored expected, and the result may decide who England play in the round of 16.
A couple of the groups have already been decided in terms of who is going through. Uruguay and Russia will progress from Group A whilst England and Belgium will follow from Group G. However, whilst Croatia are almost guaranteed to finish top of their group, both Nigeria and Argentina have a chance of making it through (Argentina’s chances are just over 50%).
As many people may guess anyway, Brazil are still the most likely winners of the whole tournament, with a 30.6% chance. However, this number is not particularly high, meaning that even though they’re the favourites to win the competition, it’s still more likely for them to not win it than for them to win it. Spain are the second most likely team to win it with a 16% chance.
Despite England’s 6 goals scored against Panama, they still rank only seventh in strength of attack. However, the fact that they have the third strongest defence makes them the fourth most likely team to win the tournament
Posted on June 19th, 2018
Social media platforms such as Twitter are a common outlet for discussion about the World Cup. The patterns and nature of the social media content can tell us a lot about how people respond to different teams and events in the World Cup.
The number mentions of “#WorldCup” spike every time an interesting event occurs at the World cup. The size of the peaks provide an indication of the events that most sparked discussion on Twitter. Harry Kane’s winning goal from last night is the 5th most discussed World Cup event on Twitter, after 3 goals from the Portugal vs Spain match and the final whistle sealing Germany’s loss in their opening game against Mexico.
We can home in on how Twitter responded to the England Tunisia game. The graph below shows how the twitter activity volumes of tweets mentioning the England and Tunisia evolved through the course of last night’s game.
England was mentioned most often immediately following the Harry Kane goals, with his second goal eliciting a stronger response than the first. Similarly Tunisia mentions were highest immediately following their goal. The responses to non-goal events such as Sterling and Lingard’s missed opportunities can also be seen in the graph.
Sentiment analysis on these tweets reveals that England fans were getting increasingly unhappy with the team over the course of the game until Harry Kane’s late winner brought comment sentiment polarity back up to a level slightly higher than pre-match levels.
Overall, the England vs Tunisia game was the third most discussed match of the World Cup. It will be interesting to see how Twitter will respond to England’s other group stage fixtures.