A belief that was never tested
"If you don't score, you get scored on." Commentators repeat it after every missed chance, as if it were a law of physics. Yet nobody seems to have seriously tested it against data.
This project takes that belief — shared by generations of fans and coaches — and gives it the treatment it never got: a series of independent statistical tests, each designed to be hard to pass by chance.
Understanding xG (Expected Goals)
What it actually is
The probability that a given shot ends up in the net, calculated from thousands of comparable shots (distance, angle, type of play).
How it is calculated
A statistical model trained on StatsBomb data assigns a value between 0 and 1 to every historical shot, based on its characteristics.
Why it matters here
It lets me define a 'big chance' objectively (xG ≥ 0.4) instead of relying on a commentator's gut feeling.
Its limits
xG ignores fine-grained tactical context (defensive pressure, fatigue) — one more reason to cross-check with several methods rather than trust it alone.
Seven layers of verification
A single test can mislead. Seven independent tests, all pointing the same way, are much harder to dismiss.
Event study
Comparing the concede rate in the 5, 10 and 15 minutes following a missed vs. converted chance.
Score-state stratification
Controlling for match state (leading, tied, trailing) to isolate the real effect.
Permutation test
10,000 random permutations to build a reference distribution under the null hypothesis.
Multiple-testing correction
Benjamini-Hochberg correction to avoid false positives from the large number of comparisons.
Logistic regression
Standard errors clustered by match, so correlated observations aren't double-counted.
Cross-validation
GroupKFold by match, evaluated on AUC and Brier score, to check out-of-sample robustness.
Bernoulli null model
500 simulations of a world with no "punishment" effect, compared against the observed result.
Five counter-intuitive findings
No "curse" of the missed chance
The concede rate after a big chance is statistically identical whether the shot was scored or missed — see the chart below.
Concede rate in the 10 minutes following a big chance (xG ≥ 0.4) or a penalty
Missing a penalty actually protects you
Across 658 penalties, the following concede rate is lower after a missed penalty (5.2%) than after a scored one (8.7%) — the opposite of the myth.
Barrages of shots don't break defenses
The concede risk stays flat around 14%, whether a team has missed 0 or more than 10 consecutive chances in the match.
Holds across 10 competitions and 66 years
Isolating each competition (including La Liga, the Premier League, Serie A, the Bundesliga, Ligue 1, and the World Cup), 7 out of 10 show a mildly protective effect, 3 show no effect — none show a significant positive effect.
Simpson's paradox in action
At the season level, the most 'wasteful' teams concede slightly more (correlation of 0.31) — but that correlation completely disappears when you look minute-by-minute, inside individual matches. That's the real statistical trap behind the myth: mistaking an aggregate correlation for a causal mechanism.
Open data from StatsBomb — 7 Jupyter notebooks, 15 figures