Why predicting football statistics is not entirely easy

If you came to the website Corner-stats.com, then most likely you are a fan of numbers and are interested in football statistics. Perhaps you enjoy discussing upcoming matches with friends and giving your expert opinion, or perhaps you bet on football and want to make a steady income from it. But correctly predicting the outcome of a football match in general or a specific statistical indicator (shots, corners, cards, offsides, etc.) is not entirely easy.

Let's look at this using corners as an example.

Let's start with the fact that corners are a side effect of other targeted actions of the team (shots, crosses, passes into the penalty area, etc.). That is, it is rare to see a team playing purposefully to earn a corner. As an exception, we can only remember Eibar in the Spanish Primera Division in the 2020/21 season (Eibar had the 3rd highest (after Real and Barcelona) team total corners in LaLiga (5.18), and, by the way, in the end took last place and flew to Segunda).

So, as mentioned above, corners occur as a result of shots (blocked or saved by the goalkeeper), crosses (blocked or cleared) or other actions on the flanks (unsuccessful dribbles, passes, interceptions, etc.). By the way, you can use the Reason for Corner filter on the website Corner-stats.com.

In turn, for a shot, cross or other to occur, the team needs to organize an attack on the opponent’s goal. Recently, on the Corner-stats.com website you can study the statistics of a team’s attacking actions using the Dangerous Attacks indicator.

If we go even further, we can come to the conclusion that the number of dangerous attacks of a team depends on its tactic for the game, as well as on the tactics of the opponent. The defensive line, intensity of pressure, tactics of holding the ball, etc. determine the number of dangerous attacks.

Thus, the formation of a corner can be represented by the following diagram:

Tactics for a game -> Dangerous attacks -> Shots, crosses etc. -> Corners

When moving from stage to stage, we have a certain conversion, which can be calculated based on statistics or estimated based on information about the match. But at each of these stages a failure can occur. You can correctly predict the tactics for the game, but the players on the field for various reasons will not be able to implement it. Or we will correctly predict the number of dangerous attacks by the team, but due to the unsuccessful actions of the attackers we will not receive the desired number of shots. Of course, we may be lucky when a failure at one stage overlaps with a failure at another stage in the other direction, and we get what we predicted. This is the case when minus for minus gives a plus :).

So, what conclusions can be drawn from this material that will help to better predict football statistics:

• the outcome of a statistical indicator of a football match is the result of many factors, which in turn depend on many other factors
• it is impossible to cancel the will of luck (the theory of probability), so you can make a mistake in the forecast, even if all factors are predicted correctly
• you can only understand whether you are good at predicting football statistics over a long distance. In this case, first of all, you need to look at whether you are correctly predicting the factors that generate the desired statistical indicator. If you can do this, then you are guaranteed a positive result over the haul.

We hope you found this analytical material interesting and will be able to benefit from it. Have a good football!