# Per 90 Stats Explained

You are probably already using statistics to help you select fantasy players, but you might not be familiar with per 90 stats. In this article I will explain why per 90 stats are much more valuable than simply looking at total numbers, which should help you avoid the common traps that most people fall into.

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## Why Looking at Total Numbers Isn’t That Helpful

The first mistake that almost everyone makes when they use statistics is that they look at the total numbers instead of converting them to rate statistics. Here is an example of a tweet that I saw the other day:

Can you spot the problem with this? It might look like I am picking on WhoScored a bit, but unfortunately they are not the only culprit. The information here is basically useless. Firstly, I am not even sure I know what the tweet is trying to tell me. Is it suggesting that Williams and Terry are elite at passing the ball sideways or back to the keeper? Who knows. The main issue with it, though, is that it doesn’t consider the number of accurate passes in terms of minutes played.

The 2009/10 season was the first time Opta data became public. Since then, John Terry has played 18928 minutes in the Premier League. Ashley Williams has only been in the league since 2011, when Swansea were promoted, but he has actually logged more minutes than Terry, 19429 in total. It therefore makes complete sense that Williams has made more passes than Terry, and it also makes sense that these two players have made more passes than anyone else because they have played so many minutes in the league! If we just look at total numbers without considering minutes played we could argue that Cristiano Ronaldo is a worse Premier League goalscorer than Emile Heskey because he only has 84 goals compared to Heskey’s 111! Of course, we all know that Heskey was actually better, but that’s beside the point.

It’s hard to argue with those numbers, right!? I think we all know who the better Ronaldo is now…

## Converting Totals to Per 90 Stats

To get a number that we can use, we need to normalise the stats for time. The current standard is to use ‘per 90’ units, which tell us the production of a particular stat over a 90-minute period. This is much easier to read than just looking at stats on a per minute basis. To convert totals to per 90 units, simply divide the total by the minutes played and multiply by 90. Let’s convert the numbers for Williams and Terry to per 90 units to illustrate:

Williams: accurate passes inside own half per 90 = (7315 passes / 19429 mins) x 90 = 33.9

Terry: accurate passes inside own half per 90 = (6705 passes / 18928 mins) x 90 = 31.9

We can now see that Williams does make more accurate passes inside his own half per 90 minutes than Terry, but that’s all we know. We don’t know how many inaccurate passes each player makes, the difficulty of these passes, how beneficial they were to the team, the average length of pass, the influence of tactics etc. What we could do now, though, is actually compare these numbers to the other centre-backs in the league properly if we thought it was worth doing (it probably isn’t). Here is a follow up tweet:

If we normalise the numbers for time played, we can see that Vertonghen has actually made more of these passes than Williams per 90 minutes in that time frame:

Williams: accurate passes inside own half per 90 = (2068 passes / 6399 mins) x 90 = 29.1

Vertonghen: accurate passes inside own half per 90 = (1980 passes / 5492 mins) x 90 = 32.4

## Conclusion

Normalising for time played is the only way to accurately compare statistics between different players. Don’t fall into the trap of using per game numbers instead, as these are also flawed. It should be obvious that it’s not fair to compare 10 games of a regular starter with 10 games of a sub, but many people seem oblivious to this fact. Make sure to always look at per 90 numbers whenever you are using stats and you will likely have an advantage over your fantasy football opponents.

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