Possession Analysis: A Closer Look

There is no shortage of analysis done recently on the fact that possession statistics tend to be misleading. A while ago, I looked at how teams with higher rates of possession in the MLS do not tend to win more games. Similarly, the Climbing the Ladder blog on the MLS website recently did analysis and found very similar results. Devin Pleuler (@devinpleuler) has done even more analysis on why possession stats are misleading for his Central Winger blog on the MLS website. On his personal blog, Devin has also looked at possession efficiency and how it relates to winning. Even more, the 11tegen11 blog (@11tegen11) has written about some interesting points on how to better analyze possession. I'm sure there are even more that I have forgotten to list here, but you get the point.

Swansea City, the "Welsh Barcelona"

Possession, Does it Matter?

Recently, I've started to question simply looking at percent possession during an entire game. It seems too broad an analysis to yield any significant or insightful results. Inspired by another one of Devin Pleuler's posts, I have looked at possession more specifically within a game. Instead of looking at how possession relates to results as a whole, I've broken down each game to try to understand how keeping the ball within a specific segment of a game changes a club's chances of scoring. Within the EPL, does a long spell of possession mean a team is more likely to score? If the answer is yes, it could point to the fact that possession actually does matter, albeit at a much smaller level. 

Methodology

To do this, I have broken down passing patterns within specific Premier League games. Instead of looking at possession as a whole, I looked at the past 25 passes, and who made them. As the game progresses and passes are made, I found the difference in passes in the last 25 passes between the two clubs. For example, the home team could have completed 15 of the last 25 passes, while the away club completed the other 10. This would give us a difference in passes of +10, as the home club completed 10 more passes than the away club. As you might expect, this is a constantly fluctuating number, which changes from positive to negative many times throughout the game.

My idea is to graph this pass difference number throughout the entire game, and mark where goals occurred. My hypothesis was that a club would tend to score when they had had the majority of the last 25 passes. In other words, having possession would tend to increase a team's probability of scoring.

RESULTS

As it turns out, this hypothesis tends to be true. The key word here is definitely tends. Of course, there are always going to be goals where a team scores off a counter-attack. However, it seems that clubs that have dominated possession recently within the last 25 passes are likely to score. When teams do not have much possession of the ball, they are less likely to score. While you may be thinking to yourself that this is nothing new, it does seem to go against the results saying that possession does not matter. It seems that while general possession may not matter, specific possession has a big influence on scoring. 

Below are some examples of the graphs I was looking at when making this analysis. A positive possession difference indicates that the home team has had the majority of passes within the last 25 passes, while a negative possession difference indicates that the away team has had the majority of recent passes. The vertical red lines indicate when a goal was scored; the ones starting at the midline and going up are goals scored by the home team, while the ones starting at the midline and going down are goals scored by the away team. Clearly, there are a few times when goals seem to have come when a team was losing the recent possession battle. For the most part though, it seems that my hypothesis above holds true. 

GRAPHS

Only 25?

One criticism of this approach may be that looking only at the past 25 passes may be too small. Admittedly, there is nothing special about the last 25 passes, I just went with that number. To check the robustness of the results, I did the same analysis, this time with the last 50 passes. It turns out that looking at the difference within the last 50 passes yields very similar results. Of course, the graphs are slightly different, but clubs still tend to score when they have had the majority of the recent possession. 

Conclusion

Based on the graphs above, it seems that possession does matter, though at a much smaller level than what we normally look at. While the overall possession percentage within a game tends to be misleading, more specific possession analysis within the game shows that clubs tend to score when they hold the majority of possession. If Stoke City is playing Arsenal, they are likely to be dominated when looking at possession percentage as a whole. In this way, possession is useless for analyzing the game. However, if we break possession down like above, it's likely to be the case that possession is important for Stoke, just in much smaller intervals within the game.