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The team that scores first in a football match wins a clear majority of the time, typically a little under seven in ten league games, with draws taking most of the rest. Match timelines on RubiScore show when each opening goal arrived, and that timing, along with who scored it, shapes what the goal is really worth.
This data-study asks one question: how much of that win rate is caused by the goal itself, and how much simply reflects which team was more likely to score it in the first place? It covers what the data captures, what it shows, the main confounders and how to separate cause from signal. Fixtures, results and match timelines are available at https://rubiscore.com for checking how any opening goal played out.
"Teams that score first win most of the time" sounds like proof that the first goal is decisive. It is not, on its own. Stronger teams score first more often, and stronger teams also win more often. Even if the opening goal changed nothing, the team that scored it would still win far more often than it lost.
The useful question is narrower: compared with what was expected before kick-off, how much does the first goal move the odds? That gap, not the raw win rate, is the goal's real value.
Studies of scoring first rely on event data that records the minute of every goal. From that, analysts identify which team opened the scoring and how the match ended, then split the results by context. The most common splits are:
Goalless draws drop out, because nobody scored first, so the percentages describe matches with at least one goal.
A broad public comparison comes from the CIES Football Observatory, which analysed domestic league matches in 92 top divisions between January 2015 and December 2019. Across those competitions, the team that scored first won just under 70% of the time on average. League values ranged from about two-thirds in Chile to about four-fifths in Moldova. Among the big five European leagues, the figure ranged from 71.1% in the Premier League to 67.8% in the Bundesliga.
A peer-reviewed study in Frontiers in Psychology looked at 1,116 Chinese Super League matches with at least one goal from the 2014 to 2018 seasons, and it reported all three outcomes. Teams that scored first won 66.31% of those matches, drew 20.70% and lost 12.99%. That pattern, with draws taking most of what is left and defeats relatively rare, is the shape behind the claim that scoring first is worth so much.
The headline figure mixes two different things.
A first goal reveals information. It suggests the scoring team was probably the stronger side, or was having the better day, before the ball crossed the line. The same Chinese Super League study shows how strongly context shapes the result. High-budget teams that scored first won 76.10% of the time, compared with 63.47% for low-budget teams. Home teams that scored first won 71.94%, while away teams that scored first won 58.60%.
The CIES club figures point the same way. Over 2015 to 2019, Paris Saint-Germain won 89.9% of league matches in which they scored first, Barcelona 88.5% and Manchester City 87.1%. Those teams were usually favourites before kick-off, so much of their conversion rate reflects who they were rather than what the goal did.
The first goal also changes the match. The scoring team now needs only to avoid conceding twice to win, and the opponent must score just to draw. The clock starts working for the leader. That change is real, but it can only be measured against what was expected before the goal.
The cleanest approach is to start from a pre-match baseline, such as a rating model or market-implied probabilities, and ask how much the goal moved it. A hypothetical example, with illustrative numbers rather than output from any specific model, shows the idea.
Team A starts a match with a pre-match win probability of around 45%. It scores in the 20th minute, and a live model now rates its chance of winning at around two-thirds. The goal is worth roughly 20 percentage points. If Team A wins, the record says "scored first, won", but much of that outcome was already likely.
Now take Team B, a clear underdog at around 20% before kick-off, which also scores in the 20th minute. Its win probability rises sharply, but the stronger opponent still has 70 minutes to respond, so Team B may remain short of even odds. Both teams scored first. The goal changed their positions by very different amounts, and the raw win rate hides that difference completely.
The same goal is worth more the later it comes. A 1-0 lead in the 85th minute leaves the opponent almost no time; a 1-0 lead in the 5th minute leaves almost a full match. The Chinese Super League study found that each minute later the first goal arrived was associated with a small increase in the scoring team's average probability of winning, about 0.28 percentage points per minute. It also found that earlier first goals were associated with larger final goal differences, which fits the idea that an early goal leaves time for the match to open up in either direction.
Once a team leads, it usually drops deeper and accepts less possession, while the trailing team pushes forward. Shot counts after the first goal therefore tend to favour the team that is behind. Part of the goal's value is spent buying that defensive position, and whether the trade works depends on the quality of chances conceded, which expected goals captures better than raw shot totals.
Several factors complicate any simple reading:
Goals are scarce in football, and most matches contain only a few of them. That scarcity is why one goal moves the odds so much: in a high-scoring sport an early lead is a small share of the final total, while in football it can be a large part of it.
This is also why live win-probability models are the right tool for the question. They combine the current score, the time remaining, pre-match team strength and, in better models, venue and red cards. The value of any goal can then be expressed as the jump in win probability, or in expected points, at the moment it was scored. Expected points convert the probabilities into league currency: three points times the chance of winning, plus one point times the chance of drawing.
Match pages on RubiScore cover most of these checks through the match timeline, lineups and match statistics such as shots and xG, while league tables and head-to-head records help frame the pre-match baseline.
Scoring first is valuable. Across 92 top divisions, the first scorer won just under 70% of league matches on average, and in the Chinese Super League sample, draws accounted for most of the remaining results. But the raw figure overstates what the goal itself is worth, because the teams that score first are disproportionately the teams that were already likely to win.
The more accurate answer is that the first goal is worth the difference between the win probability before it and after it, and that difference depends on the minute, the gap in strength, the venue and the competition. No public study isolates it perfectly, and estimates depend on the model used, but separating signal from cause turns a familiar statistic into a useful one.
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