France Football recently unveiled their 30-man shortlist for the prestigious Ballon d’Or award. The Ballon d’Or is given to world football’s best men’s player, as voted for by football managers and journalists alike.
Now I’m sure you’ll already have an opinion on who you think should win it, and my colleague Dave Willoughby’s recent blog may have influenced your decision a little, but I’d like to extend that by giving you a completely statistical perspective on the nominees. I’m going to be using StrataBet’s unique data to compare all 30 shortlisted nominees across a variety of metrics, including goals scored, primary assists and secondary assists, while looking at their expected values for each of these things as well.
Before we get into that, let’s start with levelling the playing field by measuring how many minutes each player has played. We’ll use this data to normalise each metric so that we’re making sure we’re being fair to all 30 nominees.
StrataData handily covers the domestic league competitions of all of the nominees (English Premier League, German Bundesliga 1, Spanish La Liga, Italian Seria A and the Portuguese Primeira Liga), as well as the UEFA Champions League and Europa League. So here’s the amount of time each player has spent on the pitch in 2016 so far:
Toni Kroos, Antoine Griezmann and Manuel Neuer have had a busy year, playing 3732, 3679 and 3651 minutes respectively, while the current Ballon d’Or holder Messi is 17th on the list, having only played 3050 minutes in a somewhat injury hit year.
Now that we know how long each nominee has spent on the pitch, let’s use goals as the initial metric to rank and compare them.
To understand the performance of a player, I’ve calculated the expected number of goals per 90. This is a fairly common metric these days but my number contains a fair degree of inimitability, as StrataData allows us to calculate expected goals on the actual number of goals scored in addition to the number of chances each player has had.
At the most elementary level it is key to understand that every goal is a chance, but not every chance is a goal.
Combining chances not scored with those that are scored allows us to work out what a player is expected to score given the overall number of chances they get. I have worked this out using the average conversion rates of our six chance categories, labelled Superb (~75% conversion), Great (~40% conversion), Very Good (~25% conversion), Good (~15% conversion), Fairly Good (~8% conversion) and Poor (~2% conversion), summing a player’s total chances per 90 by conversion rate rather than by category.
This has allowed me to weight each player’s chances and goals by the quality of chance to provide a firm expected goals number. This is an important metric to uncover the finishing efficiency of our nominees and is easy to recognise when plotted alongside actual goals scored.
As such, the following graphic outlines the (normalised) number of goals scored per minutes played, with the green bars representing the number of goals per 90 and the yellow bar the expected number of goals per 90 for each player:
What strikes me here first and foremost is just how effective Lionel Messi remains, which I appreciate is news to nobody. Considering he was 14th in the minutes played ranking, he jumps to number one for goals scored per 90 and is followed by Barcelona teammate Luis Suarez. Gonzalo Higuain is third with just under a goal per 90, while Cristiano Ronaldo, despite playing the fifth most number of minutes out of the nominees, is down in fourth after normalising his goals scored by minutes played.
The relationship between the green (goals) and yellow bars (expected goals based on the chances they have) is also worth noting. For the majority of the nominees, the green bars are taller than the yellow bars. This highlights the attacking and finishing prowess these players have on the pitch, as they are essentially over-performing to a point where they are converting more than would be expected. This is not true for all of the nominees however, with Pierre-Emerick Aubameyang, Neymar, Jamie Vardy, Thomas Muller and Zlatan Ibrahimovic scoring fewer goals than the chances presented to them should have produced. Aubameyang and Ibrahimovic are the biggest culprits here, but keep getting into the positions to score and there is still plenty to be said for that.
Let’s look at primary assists next, and for this we are investigating the overall ability of the nominees to provide scoring opportunities for their teammates. This is captured by assists (if their teammates score) and chances created (if they don’t).
For clarity, it’s important to note here that while assists are taken from goals only, expected assists are taken from both goals and chances. Ultimately we want to ensure that we are rewarding the nominee for his creative ability and not punishing him for a teammates’ poor finishing, and with that in mind I have sorted the data according to expected assists rather than actual assists.
Remember that StrataData captures chances in six categories, labelled Superb (~75% conversion), Great (~40% conversion), Very Good (~25% conversion), Good (~15% conversion), Fairly Good (~8% conversion) and Poor (~2% conversion). I will be using the sum of chances created by their average conversion rates to rank the 30 nominees, again normalising for minutes played:
Lionel Messi again tops the ranking for expected assists and is again assisting more than he “should be”, with Barcelona teammate Neymar joining him to make up the top two. West Ham’s Dimitri Payet and Juventus’ Paulo Dybala deserve great praise here, as they are 21st and 27th out of 30 for minutes played but third and sixth on the list for assists, respectively.
It is also worth noting that the top three players for assists are Barcelona’s fearsome strikeforce of Messi, Suarez and Neymar. This trio also convert the chances created by one another more than they miss them, which in turn helps their teammates to perform well in this ranking category.
This section is probably where you would expect to see attacking midfielders coming to the fore, and this is highlighted by the fall of out-and-out strikers such as Sergio Agüero, Robert Lewandowski and Higuaín, who drop down the ranking for expected assists. Unsurprisingly midfielders such as Kevin De Bruyne, Paul Pogba and Kroos replace them near the top, demonstrating how important it is to consider metrics beyond the scoring of chances to properly evaluate a player’s importance to his team.
With this in mind, another unique facet of StrataData is the capturing of secondary assists, a key pass (or action) that occurs directly before the assist. This plays an important part in evaluating an effective attack, as it allows us to capture the build-up to a goal or chance. Secondary assists are quite rare but do provide a nice level of insight into those players who play “the pass before the pass” and I have used this metric to rank the 30 nominees once more, again adjusting for minutes played:
De Bruyne leads the secondary assists ranking, which highlights his importance to the strength of Manchester City’s attack, being the creative force early in the earlier moments of chance creation. Next in line for secondary assists are Neymar, Gareth Bale and Messi. The Barcelona effect could be at play again here, but it’s worthy of note that Suarez hasn’t yet registered a secondary assist in this calendar year.
Please let me take a moment to give some appreciation to Hugo Lloris now too, as he is the only goalkeeper to register a secondary assist (or to appear on any of the graphs to date for that matter!)
At Stratagem we also believe that a sound disciplinary record should be taken into account when assessing the potential Ballon d’Or winner, given their status as role models and ambassadors of the beautiful game. As such, here I’ve simply counted the number of yellow and red cards each player has received during the calendar year so far (across the competitions outlined above) and again adjusted for minutes played. Here is the ranking:
Ah, Sergio Ramos. Could it be anybody else? Real Madrid’s centre-back tops the list for both yellow and red cards per 90, with Arturo Vidal and Luis Suarez in second and third place. Suarez was building himself a very solid case for consideration to this point, but it appears his indiscipline on the field is a still a factor that will count against the Uruguayan when it comes to awards of this nature. Finally, current Ballon d’Or holder Messi is ninth on the list with previous winner Ronaldo in 17th, which is the first real edge the Portuguese has had over the Argentinian so far.
Although I have endeavoured to analyse data beyond goals scored and assists made, it’s clear to see that there is a core group of players who sit around the top of each key category. This core group includes the Barcelona trio of Messi, Suarez and Neymar, whose attacking potency clearly allows them to rack up the numbers compared to players from less dominant teams. These players are clearly performing at an incredibly high level in a team with less exceptional teammates, which is arguably more impressive.
For these reasons Messi, Ronaldo, Suarez, Neymar and Payet make up the players who have most impressed me from this initial analysis. Has anyone else stood out for you? If so, please let me know by contacting me on Twitter (username below!)
Finally, given that we’ve talked about positional play and impact, I do think it’s unfair to focus only on attacking prowess as I seek to answer the question of who should win the Ballon d’Or, especially when we have four goalkeepers in the fold. For that reason part two of this series will focus primarily on Gianluigi Buffon, Manuel Neuer, Rui Patricio and Hugo Lloris. Let’s see if any of them can make a jump onto my five-man shortlist.
Until next time!
Sagar Jilka (@DrSagarJilka)
PS: If you’re wondering what game Lloris registered his secondary assist in, it was Tottenham’s 3-0 home win over Bournemouth on the 20th March.