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1990 – 2026 · A Data Story

Sent On to Miss?

Managers gamble on fresh legs for the shootout. Across 35 years of penalties, does the substitute gamble actually backfire?

72.0%
baseline conversion (all kicks)
57.1%
extra-time substitutes (105'+)
50.0%
dying-minutes subs (110'+)
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The 119th-Minute Substitution

It is a move we see more, not less. In an analytics era fixated on the highest-percentage option, managers increasingly send on a fresh, specialist taker in the dying minutes, purely for the shootout. On 29 June 2026 the Netherlands did exactly that, then watched substitute Justin Kluivert strike the post as they went out of the World Cup. England fans need no reminding of Euro 2020, when Marcus Rashford and Jadon Sancho came on in the 119th minute and both failed.

There is something quietly cruel about it. The player barely touches the game; a few minutes of cold legs, maybe one sprint, and then the whole tournament rests on his single kick. So does the gamble actually work? I built a dataset of 840 shootout kicks from 88 men's international shootouts (World Cup, Euros and Copa América, 1990–2026) to find out.


How Often Does a Shootout Penalty Go In?

Before judging substitutes, we need the yardstick. Across all 840 kicks in the dataset, the overall conversion rate is 72.0% (95% confidence interval 68.9%–75.0%). Roughly three in four shootout penalties are scored, so missing is the exception. That is exactly why a missed sub stands out.

For scale: Lionel Messi, for many the greatest of all time, has converted about 78% of his career penalties (114 of 147, shootouts aside), barely above this shootout baseline. The spot-kick humbles almost everyone.

72.0%
all shootout penalties
(840 kicks)
72.8%
taken by a starter
(486 kicks)
67.3%
taken by a substitute
(269 kicks)

The Cost of the Late Gamble

Line the groups up against the 72.0% baseline (dashed) and the pattern is stark: the further a taker sits from having started the match, the less often the kick goes in.

The late groups are subsets of all substitutes and carry small samples (dying-minute subs: n=20), so read them as indicative.


Conversion by Role

Each taker is labelled by how they got onto the pitch: a starter, or a substitute grouped by when they came on. The dashed line is the 72.0% overall baseline.

RoleKicksScoredConversion95% CI
Starter48635472.8%68.7%–76.6%
Sub before 90'20313868.0%61.3%–74.0%
Sub 90–104'312374.2%56.8%–86.3%
Sub in ET (105'+)352057.1%40.9%–72.0%

A few older Copa América matches lacked published lineup data; those kicks are counted in the baseline but excluded from the role split. Lineups for the live 2026 fixtures are taken from match reports.


It's the Extra-Time Sub Who Pays

It is not substitutes in general who falter. Across all subs the gap (67.3% vs 72.8% for starters) is only borderline. The effect concentrates in the players sent on late: extra-time substitutes convert just 57.1%, and the dying-minutes specialists brought on at 110'+ manage only 50.0%.

Because the hypothesis is directional (subs are predicted to do worse, not merely differently), the one-sided test is the relevant one; the stricter two-sided figure is shown too.

ComparisonConversiontwo-sided pone-sided pVerdict
Starters vs all substitutes72.8% vs 67.3%0.1080.054not significant
Starters vs extra-time subs (≥105')72.8% vs 57.1%0.0460.023significant
Starters vs late subs (≥110', n=20)72.8% vs 50.0%0.0260.013significant

A logistic regression agrees: being a substitute multiplies the odds of scoring by 0.77 (95% CI 0.55–1.06, p = 0.108). A substitute's scoring odds are roughly 23% lower than a starter's. For comparison, published tournament studies put substitutes near 61% against 74% for starters.

The Extra-Time Arrivals Fare Worst

Grouping substitutes by when they came on, conversion is noisy through normal time, but the players sent on in the final stretch (105–120') dip clearly below the 72.8% starter line (dashed).

The fresh-legs gamble looks worst exactly where managers reach for it most: the final minutes of extra time.

Every Extra-Time Sub Who Took One

The closest cases to the hypothesis: players introduced in extra time (105'+), often with the shootout in mind. As a group they scored 20 of 35 (57.1%).

PlayerTeamTournamentOnResult
Fabián BalbuenaParaguayFIFA World Cup 2026120'❌ Miss
Simone ZazaItalyUEFA Euro 2016120'❌ Miss
Paulo DybalaArgentinaFIFA World Cup 2022120'✅ Scored
Badr BanounMoroccoFIFA World Cup 2022119'❌ Saved
Marcus RashfordEnglandUEFA Euro 2020119'❌ Post
Jadon SanchoEnglandUEFA Euro 2020119'❌ Saved
Jamie CarragherEnglandFIFA World Cup 2006119'❌ Miss
RodriSpainUEFA Euro 2020118'❌ Saved
Thomas StrunzGermanyUEFA Euro 1996118'✅ Scored
Pablo SarabiaSpainFIFA World Cup 2022117'❌ Post
Zeki AmdouniSwitzerlandUEFA Euro 2024117'✅ Scored
Trent Alexander-ArnoldEnglandUEFA Euro 2024114'✅ Scored
Justin KluivertNetherlandsFIFA World Cup 2026113'❌ Miss
Mislav OršićCroatiaFIFA World Cup 2022113'✅ Scored
ElanoBrazilCopa América 2011112'❌ Miss
Marcus RashfordEnglandFIFA World Cup 2018112'✅ Scored
Artem MilevskyiUkraineFIFA World Cup 2006111'✅ Scored
Marcus ThuramFranceUEFA Euro 2020110'✅ Scored
Nadiem AmiriGermanyFIFA World Cup 2026110'✅ Scored
Walter GarganoUruguayCopa América 2011110'✅ Scored
Ivan ToneyEnglandUEFA Euro 2024109'✅ Scored
Xherdan ShaqiriSwitzerlandUEFA Euro 2024108'✅ Scored
Lorenzo InsigneItalyUEFA Euro 2016108'✅ Scored
Milan BadeljCroatiaFIFA World Cup 2018107'❌ Saved
Henrik LarssonSweden men'sFIFA World Cup 1994107'✅ Scored
Sylvain WiltordFranceFIFA World Cup 2006107'✅ Scored
WillianBrazilFIFA World Cup 2014106'❌ Miss
Federico BernardeschiItalyUEFA Euro 2020106'✅ Scored
Marko LivajaCroatiaFIFA World Cup 2022105'❌ Post
João FélixPortugalUEFA Euro 2024105'❌ Post
Josip IličićSloveniaUEFA Euro 2024105'❌ Saved
Gonzalo MontielArgentinaFIFA World Cup 2022105'✅ Scored
Lovro MajerCroatiaFIFA World Cup 2022105'✅ Scored
Bradley BarcolaFranceUEFA Euro 2024105'✅ Scored
Thiago AlcântaraSpainUEFA Euro 2020105'✅ Scored

Baseline by Competition & Era

Conversion is remarkably stable across competitions and decades, so the substitute effect is not an artefact of one tournament or period.

CompetitionKicksConversion
FIFA World Cup30367.3%
UEFA Euro20973.7%
Copa América32875.3%
DecadeKicksConversion
1990s23179.2%
2000s14369.9%
2010s25272.6%
2020s21465.0%

Why This Isn't a Clean Experiment

A substitute is not a random starter, so part of the gap may reflect player quality rather than cold legs alone. But it often cuts the other way: the late sub is frequently a designated specialist, sent on precisely because he is one of the squad's best takers with a strong record in normal play. That even these specialists miss more here points at the conditions (a long wait, then one cold and decisive kick) rather than the player. Either way the data is observational, so the pattern is real but not proof that the substitution itself is the cause.

Scope

This analysis covers shootout penalties only. In-play penalties, taken in open play rather than a shootout, convert a touch higher (around 75% historically) and carry different pressures. Everything here is shootout-specific.

Methodology & Sources

840 shootout kicks from 88 men's international shootouts (FIFA World Cup, UEFA Euros, Copa América), 1990–2026. Each taker is classified as a starter or a substitute, with the substitute's minute of entry, by joining the shootout result to the match lineups.

Two sources. StatsBomb open data (event-level data with exact substitution minutes) is the ground truth for recent tournaments. Wikipedia knockout-stage pages, which carry both the shootout box and full lineups with substitution minutes, provide the historical coverage. The Wikipedia parser was validated against StatsBomb on the 18 shootouts present in both sources, matching 100% on outcome sequences and substitute counts.

Confidence intervals use the Wilson method; group comparisons use a two-proportion z-test (one- and two-sided) supported by a logistic regression. Lineups for the live 2026 fixtures were taken from published match reports; a handful of older Copa América matches still lacked lineup data and are counted in the baseline but excluded from the starter-vs-substitute split. The 2026 World Cup is ongoing, so figures are a snapshot.

Elisha Amir is an independent data consultant and a lifelong football fan. This piece is built on a custom dataset of penalty-shootout kicks assembled from StatsBomb open data and Wikipedia, validated across sources. All charts are interactive.