The same number means something different depending on where and how it was produced. Here are the traps we see most often.
The traps
- League and role: 0.40 goals per 90 in a league with weak defences is not 0.40 in a stronger one.
- Penalty and set-piece takers: they inflate goals and xGi without saying much about open play.
- Hot streaks: a few matches with many goals do not change the real rate.
- Transfer hype: the name rises in the news and the market prices it in. The numbers did not change.
- Age: young players often improve and players over 31 often lose pace. The average says nothing about one specific player.
- Injury history: a return from a major injury usually means fewer minutes and lower intensity.
Penalties: an example
One match is not enough
A player with 0.30 goals per 90 is expected to score 1.2 goals in 4 matches. If he scores 5, the hot streak is 3.8 goals above expectation. One match or one week is not a sample.
What data can and cannot say
Public data shows what happened and how often. It does not show what the coach is thinking, whether the player is fully fit, or how he will play against a specific opponent. xG differs by provider. So we give a direction, not a certainty.
Data also has gaps. Smaller leagues often have no xG or less careful tracking. Comparing two providers can give a different xG for the same player.
A simple check before you trust a number
- How many minutes did he play? Under 900 is small.
- How many of the goals are penalties or set pieces?
- In which league and with which role was it played?
- Is it a hot streak or the rate of two seasons?
- Is something missing that the data does not show, such as an unreported injury?
If you cannot answer these, the right move is to draw no conclusion. Skipping a match is also a decision.