Roma grabbed a fantastic 3-1 away win over Inter Milan at the...
- Nainggolan double helps Roma beat Inter 3-1 at the Giuseppe Meazza
- Ramadan Sobhi starts in Stoke’s heavy defeat to Tottenham
- Safwat to face Gael Monfils in Dubai Tennis Championship
- Egypt U-20 draw their first game in the AFCON
- Shikabala included in Zamalek squad for Haras El-Hodood Cup match
- EFA announce date for Arab Club Championship draw
- Al Ahly and Wadi Degla fined following league match controversy
- Karim Nedved confirms receiving an offer from La Liga club
- Elmohamady plays full 90 minutes as Hull draw with Burnley
- Mamdouh Hashem: PAUC is like my family
Advanced Stats are here: Football’s ‘Moneyball’ revolution
Football’s ‘moneyball’ revolution has taken a while to get going, but is finally making its way into mainstream thinking & media. Here is a look at how advanced stats are changing the way we view the beautiful game and how teams can benefit.
Football’s number problem
Despite being one of the oldest and most recognizable sports in the world, football has always remained rooted in its traditions. Football has been surprisingly number resilient over the past 150 years, which may perhaps help explain its amazing popularity. FIFA started tracking assists in 1994! Possession, assists, shots-on-target, all are relatively new statistics that are being tracked and fed to the average fan in a much more detailed way than was possible even as early as a decade ago. Even the modern definition of formations, with four bands and ‘false nines’ are a relatively new phenomenon.
Yet despite this recent influx of numbers into the beautiful game (to the irritation of many fundamentalists) the way we understand and quantify football is still at a very low level compared to other sports such as basketball or baseball. As Jonathon Wilson, one of the leading football writers in the world, writes, “in terms of applying statistical methodology to understanding it (football), we are now only at the level doctors using leeches were in understanding medicine.”
This is perhaps best shown by the amount of incorrect football clichés the casual fan has to hear as he watches, like for example:
“Teams are always more vulnerable to concede after scoring.”
“That is a bad time to concede.”
Even worse, statistics like assists & possessions have become so widely used despite their obvious shortcomings, leading to a casual football conversations sounding something like this:
“Player X is a better passer/more valuable because he had more assists than player Y.”
“Team Z dominated team A! Look at those possession stats! They clearly deserved a win.”
Stick with us and we’ll show you why possession, statistics, & even goals (!) are misleading stats.
So why are accurate statistics important?
Statistics are important in every sport, for both the casual fan and the evaluator. For the evaluator, they provide the basis upon which he can quantify individual contributions to team success/failure. Evaluators use statistics to assess prior performance and predict future performances. For the fan, it provides context and a good base for comparison of players. Comparison is often a tricky subject in a game of multiple moving factors like football, which is what makes accurate, informational statistics all the more important
The problem with current statistics:
Despite football’s complexity, it has become increasingly clear that the statistics used by mainstream football are of a very poor level, primarily because they give no real indication of a team/player’s value & have no predictive power. In their book The Numbers Game: Why Everything You Know About Soccer Is Wrong behavioral analyst Sally & statistician Anderson tackle some of the worst offenders and prove that current mainstream statistics are outdated.
So what are the biggest problems with stats like assists, possession, etc?
The assist is a misrepresented stat, often leading midfielders to get credit for simple passes that were only goals due to the great finish of a teammate!
For example, this pass to Ronaldo was an assist by Anderson:
While this pass from Fabregas is forgotten on the score sheet due to Leo Messi (of all people!) missing the 1-on-1:
So Ronaldo rewards Anderson with an assist due to the great finish, while Fabregas misses out on it due to his striker missing!
Another problem with the assist is that often the crucial pass that leads to the goal is the pass before the assist, like this beautiful pass by Suarez that leads to a goal
Advanced Solution: Key Passes instead of assists
The advanced statistics community has replaced the value of an assist, with a key pass.
Key Pass: A pass that leads to a shot attempt &/or a quality scoring chance
So Fabregas and Suarez would both be credited with a key pass!
Modern football still uses raw statistics when comparing players, which can lead to misleading information.
2012/13 Bundesliga Stats
A quick look at the chart seems to point Ribery as the much better performer. Yet if we look at stats per minute’s things change.
Minutes Played in 2012/13
Advanced Solution: Per90
Dividing statistics by minutes and then adjusting them to fit 90 minutes seems to be the perfect way to adjust for players who play fewer minutes. Goalper90, KPper90.
Ribery Goals per 90: 0.43
Robben Goals per 90: 0.46
So the only reason Ribery has more goals are the more minutes. Robben is the more efficient scorer!
You would think goals are a statistics that cannot possibly be misleading, right? Player X has scored more goals than player Y seems like a clear-cut assessment of the player’s goal prowess (especially forwards!)
Yet things aren’t so simple. We’ve all heard this saying from a grumpy opposition fan before:
“Well he only scores so much goals because he gets so many chances!”
Advanced Solution: Chance conversion % & Clear-cut conversion %
The analytics community has come up with two metrics to better judge strikers on purely their finishing ability.
Chance conversion % is goals scored divided by the shots taken, which takes a look at the striker’s efficiency! A player who scores more goals with less shots is more efficient than a player who wastes shots to score goals.
Clear-cut conversion % is goals scored divided by clear-cut chances, defined as easy opportunities/shots from inside the 18. This stat often divides the average finishers (Giroud scored 4 of 23 clear-cut chances) from the elite finishers (Van Persie scored with 18 of his 40).
A statistic like this could also predict future performance, as last year Luiz Suarez (7 of 25) had a very poor conversion rate which cost his team, but this year he has rebounded to have a great year. An important statistic for a striker is getting these clear cut chances using his movement!
Here’s a look at both of these stats for the EPL 12/13 season
“Possession is nine-tenths of the law”
This is a personal pet peeve of mine. Inspired by the recent dominance of Spain and Barcelona with possession-based football, it seems that football has equated possession with dominance.
In their book mentioned above, Sally & Anderson proved that possession actually has zero % correlation with winning. Zero!
So what are the stats that correlate most with winning?
Advanced statistics are still trying to figure out the golden formula when it comes to winning football matches. They have narrowed down some statistics that are much correlated with performance then possession!
- Total Shots Ratio
(Shots for)/(Total shots in a match)
Stolen from hockey, total shots ratio has proven to be one of the most accurate statistics when comparing teams over long seasons. Although not relevant when looking at individual matches due to luck, studies have shown that it is repeatable, and is a good indicator of overall strength. Anything above 55% is considered very good.
Managing turnovers is actually much more important than actual possession. In their book, Sally & Anderson (mentioned above) claim that their research has shown that around a third of all goals are derived from turnovers in a team’s own half! This may explain the recent rise of pressing as well as defenders with good ball control as teams figure this out
- The 1st goal
Sally & Anderson created a stat that is named marginal points. It examined the value of scoring a goal. Obviously a goal when a team is already up 3-1 is of lesser value than a goal when the score is tied. They examined which goals in which situations added the most points for a team
So which is the most valuable goal?
According to this study Anderson & Sally this chart explains marginal value of a goal
As shown above, when tied at halftime, a 2nd half goal is worth 1.31 extra points, the most valuable goal in football. The 2nd most valuable change is scoring a 2nd goal in a game where your team was behind at halftime which is worth 1.08 extra points. On the other hand, a 5th goal after halftime (even with your team behind) is only worth 0.15 points, since the result is most probably locked up.
Therefore, players that score most of their goals when tied are more valuable than players who score other types of goals (Oliver Giroud & Jermain Defoe are examples).
These are some examples of the different ways advanced stats have started to influence our understanding of football. Although still at a relatively basic level and not without shortcomings, advanced data analysis is here to stay.
Egyptian football should take notice; build an advantage!
So what’s the point of all this you ask?
Big data has proven to be the future of all sports. The Oakland A’s were able to build a championship contending team in baseball on a limited budget using advanced statistics that other teams did not understand. The Boston Red Sox copied the models and were able to win their first title in 84 years.
Football teams are slowly catching onto the value of statistical analysis in order to make smarter decisions, and get more value for their money. Liverpool has hired scouts that use these advanced analytic tools because of their links to the Red Sox, and have enjoyed resurgence. Manchester City has a sports analytics department. Even managers (usually the most resistant), have been more open to using data to improve performance. AVB is a big proponent of advanced statistics. Roberto Martinez has a data analysis room at home that he spends significant time in tinkering with his information and trying to improve his team, an obsession that has led to his teams punching way above their weight. Petr Cech and Chelsea won the 2011 CL using data analytics, as Cech had done his homework and guessed correctly on every single penalty!
Egyptian teams do not have the money or the infrastructure to compete with European teams and National teams. However, there is no monopoly on data. Advanced analytics can help teams consistently punch above their financial weight if used, and Egyptian football directors should take note and try to build an advantage for their footballing community.