Statistics have become a part of the regular footballing conversations but which ones matter and help the usual fan understand the game better? We try to look at eight such metrics.
We at 12th Khiladi believe that football analysis should be an amalgamation of data and storytelling. Now, you might say, that’s just ‘hoity toity jargon’ to make things look better to which we will politely reply, ‘proof is always in the pudding.’
A football match is mostly defined by the score line, which could vary from being a 0-0 stalemate to a 4-1 thumping victory for either side. However, there are metrics beyond goals that have become a part of the modern-day conversations between football fans.
Chances are that you might know a lot of these metrics we’re about to mention. However, we believe that these eight metrics are imperative and highly useful for a football fan making an attempt to understand a match or maybe trying to pre-empt what will happen in the next one.
Here are eight metrics that we use a lot in our analysis and believe they’ll help any football fan:
1. xG – Expected Goals
xG is one of the most talked about statistics in modern-day football. It has crept into the everyday vocabulary of football writing, while also sparking heated debates on football games. The term stands for expected goals, and it is a statistical measure of the quantity of goalscoring chances and the likelihood of them being scored. An xG of 0 is a certain miss, while an xG of 1 is a certain goal.
An xG of 0.5 would indicate that if identical shots were attempted 100 times, 50 would be expected to result in a goal. The xG value is calculated using countless previous shots that were similar in nature, and seeing how many of those shots were scored.
Based on statistical data, for example, a penalty kick is worth 0.76 xG, and this makes sense given the fact that most but not all penalty kicks are converted. Not all shots are equal in their quality. For example, one shot might be a speculative 35-yarder and another might be an open goal tap-in.
Therefore, xG measures the quality of each shot before the player shoots, taking into account many factors, including:
- The distance from goal
- Whether the shot was with the head, or with the weaker/stronger foot
- Whether the shot was from a cross, through ball, short pass etc
- Whether there were multiple defenders in the way
2. xG OverPerformance
A more interesting statistic than just xG is xG overperformance. This statistic indicates the extent to which players outperform their xG. A good example of xG overperformance is Lionel Messi. Barring this season, the Argentinian has consistently outperformed his xG over the course of his playing career. Here’s a look at his goals vs xG comparison in the league from 2014 to 2019:
xG overperformance is an important statistic because it indicates how good of a finisher a player is. When a player consistently outperforms his xG, he is scoring more goals than he is expected to. This could indicate that he needs just half a sniff to put the ball in the back off the net.
Likewise, a player that consistently underperforms his xG by a significant margin is likely a poor finisher. While xG does not consider the quality of the player shooting, xG overperformance can give us an idea of the quality of a player.
3. PPDA – Passes Per Defensive Action
Pressing is a key element of modern football, a trait heavily adopted by some of the best sides in Europe, such as Liverpool, Manchester City, Chelsea, Bayern Munich, and Barcelona. For this reason, the statistic PPDA is of growing relevance in today’s game. This is a metric that can quantify the extent and aggression of high presses employed by teams.
PPDA = Number of Passes made by Attacking Team (opponent) / Number of Defensive Actions
Where Defensive Actions are:
• Possession-winning duels
Both values (passes made and defensive actions) are calculated in the opponent’s final 60% of the
pitch. A lower PPDA value indicates that a team is more intense in its press, because it allows the
opposition team to string together fewer passes before breaking up the play.
Here’s a look at some of the teams in Premier League and their PPDA statistics:
It’s important to note, however, that PPDA doesn’t give us an indication of the success of a team’s strategy. Rather, it’s a better indicator of the team’s style in winning the ball back. It tells us which teams are more proactive in their attempt to regain possession after losing it.
4. TSR – Total Shot Ratio
This statistic is used to measure how well teams fare in a match when it comes to taking and
How is TSR calculated?
TSR = (Total shots for)/(Total shots for + total shots against).
For example, if a team attempts a total of 15 shots on its opponents’ goal, and concedes a total of 10 shots on its own goal, its TSR is: 15/ (15+10) = 15/25 = 0.60
The only criticism of TSR is that it doesn’t account for the quality of a shot. However, although several other ratios have been developed, TSR continues to be used frequently because of its simple nature. Here’s a look at TSR and why it works:
|Team||GF||GA||GD||Shots per game||Shots conceded per game||Shot ratio per game|
|West Ham United||60||51||9||11.8||14.4||0.45|
As can be seen, for the 2021/2022 Premier League season, there was a positive correlation between
TSR and goals scored, as well as TSR and goal difference, indicating that a good TSR is likely an
indicator of a team outscoring its opponents.
5. xA – Expected Assists
xA is a statistic very similar to xG, only that it represents expected assists instead of expected goals.
This stat measures the likelihood that a pass will become an assist for a goal. It takes in consideration
multiple factors, including:
• Length of the pass
• Type of pass
• Pattern of play (open play, corner, free kick, throw-in, etc)
• Location of where the pass is made from
• Location of where the pass is received
While xG tells us the quality of a chance, xA tells us the quality of a pass. It doesn’t matter whether that
pass is converted to a shot that leads to a goal. xA only tells us how likely it is that that pass can be
converted to an assist.
The xA statistic helps in quantifying how creative a player is, regardless of the assists he makes in
a certain number of games. In reality, an assist depends heavily on the player who is shooting
the ball, and this is something that is out of control of the assist-maker. For this reason, the total
number of assists a player makes does not always tell us everything.
Here’s a look at assists vs xA for Premier League teams this season:
6. GCA – Goal Creating Actions
Goal creating actions are the last two offensive actions before a goal was scored. This is an
important statistic as, for an individual player, it indicates how much that player contributes to a
goal scored by his team, before the goal itself.
Here are the best players in the Premier League when it comes to goal creating actions:
And here’s a look at the statistics for teams:
Generally speaking, this isn’t too far off from what the final league table looks like. Wolves and
Brighton are anomalies, but barring them, no team is more than 2-3 spots away on this table from
where it stands on the final league table. The top 4 and bottom 2 is consistent, and the mid table
is also similar. This indicates that goal creating actions are a good indicator of where a team
is likely to stand on the table.
7. Progressive Passes
A progressive pass is a completed pass that moves the ball toward the opponent’s goal at least 10
yards from its furthest point in the last six passes, or any completed pass in the penalty area. It also
excludes passes from the defending 40% of the pitch.
Progressive passes are one of the most important set of passes in the modern game in order to be
a consistent and dangerous threat. In fact, around 40% of goals scored in the modern game are a
result of progressive passes. This is responsible for more goals than basic pressing, set-piece
passing, individual play, as well as a set-piece kick. For this reason, it is an extremely important
statistic to measure.
Here’s a look at players with the best progressive passing statistics in the Premier League:
Arguably the 2 best full-backs in the league, Trent Alexander-Arnold and João Cancelo lead the
way in this category. It also explains why they are considered so pivotal in the build-up play of
both their respective teams. Otherwise, the list is largely dominated by midfielders, barring a few
defenders like Andrew Robertson, Antonio Rüdiger, and Aaron Cresswell.
8. Pressures (Attacking 3rd)
Pressing, is, as discussed before, an integral aspect of the modern game. However, when it comes
to pressures, it is interesting to look at the statistics for only the attacking 3rd of the pitch. This
gives us a good idea of the way certain teams set up. The more higher up the pitch a team operates,
the more likely it is that that team is applying pressure in the attacking 3rd of the pitch.
Let’s look at the statistics for Premier League sides:
This statistic is a great indicator of a team’s style of play. From the table, we can see that
Liverpool applied the most pressures in the final 3rd of the pitch, and this is testament to the way
Jurgen Klopp sets up his side. Liverpool are a high-pressing team and the front 3 do a lot of work
off the ball.
On the other hand, Manchester United sit at the bottom end of this table. Their premier marksman, Cristiano Ronaldo, does minimal work off the ball and has one of the lowest numbers when it comes to pressures applied among all forwards in the league.
Specifically for individual players, mainly forwards, this is an extremely important statistic as players who can do good work off the ball are always a bonus, especially in the modern game.