I recently watched Tifo Football's analysis of the best progressors of the ball on their channel, Tifo IRL, and I was inspired to do an analysis myself.
I got the data from FBref's 2020-2021 stats from the Big 5 European Leagues, namely:
Before that, let's do a quick summary of the stats and terminologies used.
When defining the "best progressors of the ball", one has to understand the rules of Football/Soccer.
The aim is to take a ball from anywhere on the field and put it into the opponent's net/goal. Whoever does that more wins the match. For example, in the image below, if you win the ball from the opponent at point A, you need to move it to point B.
Hence, the idea of progressing the ball correlates to winning the match. Whoever progress the ball more from A to B creates more chances to score a goal.
Note that a player is not terrible if he's not featured here, as there are other roles they could be playing e.g. scoring goals or defending.
We'll be using two metrics that was used in Tifo's analysis:
In simple terms:
We used "per 90" in order to make it more comparative. An absolute value would favour players who played more minutes.
On top of those metrics, I'm adding these data points:
Each leagues have unique playing styles so it would be unfair to lump all players into one chart without differentiating their leagues. e.g. La Liga is a slow, possession-based league vs Bundesliga which plays a faster, open-ended style of football vs Premier League where half the team just sits in their own box
Second, if a team usually has more the ball, they naturally would progress the ball more per 90 minutes.
If we can identify players who thrive despite the team usually having less of the ball, these players might perform well when recruited into a team that has more touches on the ball.
Also, I've filtered the data to players who played over 1800 minutes of football in 2020-21 season to look at players who performed consistently. 1800 minutes = 20 full matches if played continuously (one season has 38 matches).
As with any scatter plot, the top right signifies players who performed well on both metrics, and obviously Lionel Messi is right there.
We also see other usual suspects such as
We instantly notice that the top right is mostly in blue while the bottom left is mostly in red. Blue signifies teams who have high touches on the ball per 90 minutes while Red is the reverse.
This is one factor that I thought was missing in Tifo's analysis.
Players on the bottom-right are those who progress the ball more through dribbling than passing.
Premier League fans would recognise the usual suspect — Adama Traore who is very unstoppable when dribbling at opponents. Here are the players at the bottom right corner.
An interesting player is Bryan (Eibar) marked with the red cross. He moved to Tottenham this season and his team has one of the lowest touches of the ball in the highly possession-oriented La Liga.
Tottenham, who plays a counter-attacking style, seems a perfect fit for Bryan. Tottenham's new manager was managing Wolves which is a counter-attacking team that has Adama Traore and Pedro Neto (the two red squares at the bottom).
As noted in Tifo's video, players like Bernardo Silva "cheats" the metric a bit as he often plays near the edge of the box.
In the measurement of progressive carries, any dribbles that result in the ball entering the opponent's box = progressive carries.
Therefore any analysis of football needs to be coupled with an understanding of the game.
The best kinds of pass results in the ball moving forward, just like the best kinds of car.
Nobody wants a car that drives backward better than it drives forward.
Over here, we see the best passers.
A bit of a mess here, but we see the usual suspects like:
Ridle Baku and Sacha Boey seem like exciting prospects as they are 22 and 19 years old respectively, played in a team with low touches per 90, played over 1800 minutes last season and had higher than average progressive passes.
However, I'm not too familiar with those players but would be interesting to dive deeper into their playing style and stats.
Let's imagine we're a team who has a higher than average possession of the ball and we would like to identify players who are underperforming because of their team playing a low-possession style of football.
These players would want to have more touches on the ball and can move the ball forward.
Apart from that, they probably hate their time at their current club cause fewer touches on the ball = more defending. Nobody enjoys defending when they are skilled at progressing the ball.
Here's the chart after selecting those in red.
Depending on the player our team needs, we can recruit those who are better at dribbling (bottom) or better at passing (top).
It's usually good to have both styles in a team to be adaptable to different styles.
Jack Grealish, who recently moved to the possession-heavy Manchester City, is performing well in his new team as his ability fits perfectly there. He's also known to be a very high-impact player in the low possession team of Aston Villa.
We also see Rodrigo de Paul who was a subject of interest from multiple teams in the transfer window and eventually moved to the La Liga title holder Atletico Madrid.
Hakan Calhanoglu also moved to the neighbouring Inter Milan. Apart from that, I'm not too familiar with the rest, but I'm sure they are talented players too.
However, some players have good dribbling stats because of the team's playing style. A player playing in a team with low possession has more room to dribble into, hence their stats might not translate well into teams with more possession.
Of course, we could also add a filter for age if we're looking for players below a certain age. Some teams have age requirement when recruiting e.g. Leicester City.
A similarity analysis would be useful too if a team wants to replace a particular player. I believe Manchester City's recruitment of Jack Grealish is partly because of Bernardo Silva's expiring contract, as we can see that the two players are very similar in stats.
There are also metrics like Progressive Distance if a team is looking for a deep-lying playmaker (someone who plays deep and passes a long distance forward) and Dribble Success Rate (we don't want a player who has a lot of dribbles per 90 but loses the ball a lot).
Such analysis would be misleading without accounting for more seasons, as some players could be one-season wonders. I'm sure the professional scouters do this across multiple seasons before making a multi-million dollar purchase.
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