Shots on target vs total shots: how to read the statistics
Total shots, shots on target and goals measure different events. Keep their definitions separate before comparing teams or markets.
What counts as a shot on target?
A shot on target is an attempt directed at goal. Under Opta’s event definitions, goals and shots saved by the goalkeeper belong to this category; some last-line blocks also count. A shot against the woodwork that does not score is treated differently from a save.
Check the actual provider and settlement definition. This reference explains terminology and does not imply that Cuotario uses Opta as its data provider.
Why total shots are different
Total shots include attempts that may be on target, off target or blocked, depending on the provider. A team can shoot often without directing many attempts at goal. More attempts alone do not prove that chances were better.
Illustrative example: 12 total shots, 4 shots on target and 1 goal can all describe the same match. Do not add the four shots on target to the total again.
Team statistics and player statistics
A team statistic combines its players’ contributions. A player’s output also depends on whether they appear and how long they play. Do not turn an average per appearance into an expectation for 90 minutes without checking the denominator.
Lineup similarity influences enabled expanded team markets when coverage permits. Descriptive output associated with absent players is not automatically subtracted from a projection. Individual player markets retain their separate model.
Sample, opponent and variation
Compare a team’s production with the opponent’s conceded attempts. Consider venue, earlier opponents and unusual match events. One exceptional result can greatly affect a small sample.
If total-shot data exists but shots-on-target data is missing, one metric must not replace the other. Each market has its own available sample.
Read the markets separately
Open a match from the football fixtures and review total shots and shots on target separately. Use team profiles to compare descriptive averages with model projections.
The probability and sample-size guide explains the percentages shown beside selections. A high estimated probability still allows the opposite result.