Football analytics

Enrich your
football knowledge
with stats, smart performance indexes
and data visualisation

Data science applied to football

Explore and evaluate the performances of football players and teams, through innovative indicators and user-friendly data visualisation tools. Analyse all their relevant statistics and anticipate their potential development.

The platform, fully optimised for mobile devices, takes you through a football journey, from the most simple to the most advanced analytics tools.

1. Start with the most common stats, such as the number of goals and assists.

2. Progress and find the usefulness of per-90-minutes data, allowing the full comparability of the players.

3. End the journey with one of our machine learning algorithms, for example the one which automatically finds the most similar players to any footballer, based on their performances: a very useful scouting tool for discovering unknown talents.

8,000 players and counting

Our database keeps growing and it is currently composed of more than 8,000 players, across 14 different leagues, in 9 countries.

We display the stats of all the players and the teams of the first and second divisions of England, Spain, Italy, Germany and France. Additionally, we have the Eredivisie (Netherlands), Primeira Liga (Portugal), Süper Lig (Turkey) and Jupiler Pro League (Belgium).

Soccerment Performance Rating

The Soccerment Performance Rating system ('SPR') was designed to transform complex statistics into accessible and actionable insights, to facilitate talent discovery.

We take into consideration all the available information about the technical events: all the shots, passes, launches, yellow cards, headers, dribbles - you name it - transformed into per-90-minutes stats and weighted for their importance to the team's results, with the different weights depending on the player's tactical roles.

SPRs are assigned to the footballers having played at least 270 minutes, in order to have some statistical relevance.

There are a number of adjustments we apply, to make the ratings as fair as possible. Two of these adjustments are worth mentioning: a) first of all, we adjust for the number of minutes per appearance, favouring the contributions of those players with a higher playing time per appearance; b) secondly, we adjust for the league: under the assumption that 10 goals in the English Premier League are 'worth more' than 10 goals in the Championship, we analysed how the stats change when the players move from one league to another and developed ad-hoc ratios to normalise the results.

Compare any Player with our Spider Charts

Spider Charts - in our view - are the best way to visualise performances and compare players.

We use seven indexes, derived by a series of proprietary algorithms, developed by our Research Team. Like for the Soccerment Performance Rating, we adjust our indexes by taking in consideration the league, playing time and others.

For this index, the algorithm developed by our Research Team takes in consideration all the main defensive actions (such as tackles, clearances, ball recoveries, etc), along with their end results (clean sheets, goals conceded). For the goalkeepers, it obviously takes in consideration also all the saves and the shots on target against. If a goalkeeper and/or a defender have higher-than-average success ratios on defensive actions and they are part of a team which is able to concede a few goals, then it is highly probable that they perform well on this index.

The physical characteristics of the players (including height, weight and the body mass index) are blended using the internally-developed age curves. Goalkeepers and physically-strong strikers generally do well on this index. 

Attempting 120 passes per match is not enough to do well on our Passing Index, as this favours the most audacious passes (for example, the forward passes and the long passes). The index also distinguishes for the location of the passes, obviously applying higher coefficients to the ones made in the last third of the pitch. Playmakers, like Frankie de Jong, Sergio Busquets, Marco Verratti and Jorginho generally do well on the Passing Index.

If you are looking for a creative attacking midfielder or winger, keep an eye on the Vision Index. Our Research Team developed it by putting a lot of emphasis on through balls, chances created and second assists, apart from – of course – assists. Kevin de Bruyne and Dimitri Payet are often among the main contenders for the top spot on this index. 

The Attacking Index, unsurprisingly, favours the strikers who are able to: often touch the ball in the opposition box, take many shots from favourable positions, have a high shooting accuracy and – ultimately – score a lot of goals. Robert Lewandowski, Cristiano Ronaldo, Kylian Mbappé and Sergio Agüero are often top-ranked here. Not a surprise, right?

It is not only the number of dribbles that a player attempts, but the percentage of the successful dribbles, to make a player King of the Dribbling Index. At the time of writing, Lionel Messi is King, with 7.9 attempts per 90 minutes and a 74% success rate. 

If a player is much taller than average, wins more aerial duels than average and – from time to time – also scores with magnificent headers, then it is highly probable to see the player topping the Heading Index. Definitely an Index for the Chris Wood’s and Leonardo Pavoletti’s of the world. For a full list, see our research here

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Compare any Team with our Radar Charts

While for the players we use the Spider Charts, for the comparison of the teams we make use of the Radar Charts. Yes, they look similar. There is one big difference though: whilst the former display our Performance Indexes, the latter show the teams' six key stats per 90 minutes.

We compare the team's key stats versus the average of all the teams of the same league. In the exhibit below, for instance, the key stats of Borussia Dortmund (in blue) are compared to the average stats of the teams participating to the German Bundesliga (white). The much wider area of Dortmund's radar chart clearly correlates with the team's good Bundesliga position (third behind Bayern Munich and RB Leipzig, at the time of writing).

In the exhibit below, on the right of the Radar Chart, some more key stats - expressed in per-match data - deepen the provided analysis. In order to assess the defensive skills of the teams, we put the number of goal against, the shots against, the shots on target against and the saves ratio.

The build-up ability is represented by the following stats: ball possession percentage, the number of successful passes in the own half and in the opposition half and passing accuracy.

Finally, the offensive production is synthesised using the following KPIs: total shots and shots on target per match, with the shooting accuracy and the number of goals per match.

When the stats better than the average, they are highlighted in green, while they are red if worse than the average. In the specific case below, out of 12 KPIs, Borussia Dortmund is much better than the average Bundesliga team 9 times. There is only one KPI where BVB underperform and that is the saves ratio, of 54.3% vs 67%.

Top 11 selections

Our mathematical models automatically select the top seasonal performers for every team and every league in our database.

We use a 4-3-3 formation and select the players displaying the highest SPRs, using the following scheme:
One goalkeeper, the best right back (or right wing-back), the two best centre-backs, the best left back (or left wing-back). In midfield, we take the top three midfielders (defensive mid and/or attacking mid and/or central mid) and the best three forwards (strikers and/or central forwards and/or wide forwards).

Take for example the Top 11 selection for the Premier League, as of 20 February 2020. The top goalkeeper, according to our rating system, is Liverpool's Alisson. Liverpool displays other three defensive players: Trent-Alexander Arnold (top SPR among right-backs), Virgil Van Dijk (top SPR among centre-backs) and Andrew Robertson (top SPR among left-backs). Leicester's Çaglar Söyüncü (second-highest SPR among centre-backs) completes the defence.

In midfield, we take the top three SPRs among the macro-group "Midfielders", which includes the defensive midfielders (DMC), central midfielders (CM) and central attacking midfielders (CAM). Manchester City's De Bruyne and Rodrigo display the two highest SPRs among Midfielders, followed by Chelsea's Jorginho.

In Attack, Manchester City and Liverpool again dominate the scene, with Sergio Agüero, Mohammed Salah and Sadio Mané displaying the top 3 SPRs of the macro-group "Forwards" (strikers, central forwards and wide forwards).

Our passion will drive a continuous improvement

We are crazy about football. That is why we developed our analytics tools. We want to know more, to better understand the Beautiful Game, to know every player in every league. We want to be on top of things and even anticipate the top clubs on discovering the next football star.

Our passion is the main driver for the continuous improvement of our tools. The website will be changing fast in the next few months. Are you ready to grow with us?

Talking About Us

Do you need additional details? Please have a look at our F.A.Q.