Momentum or Myth? Does a Big Win Carry Into the Next Game?

Beat a strong team and confidence should rise. Lose to a weak one and something must be wrong. At least, that is the story basketball fans tell themselves. But does the next game actually confirm it?

Momentum is one of basketball's most familiar ideas. A team beats a top opponent and suddenly it feels dangerous. Another team suffers an embarrassing loss against a weaker opponent and the assumption is that the damage may carry into the next game.

There is an intuitive logic to it. Confidence, pressure and team chemistry are real parts of sport. The problem is that basketball data contains another powerful force: team quality.

A strong team is more likely to produce an impressive win in the first place, and it is also more likely to win its next game. If we ignore that, ordinary team strength can easily look like momentum.

The Raw Numbers Look Like Momentum

We classified opponents using their strength before the game. Teams in the top quarter of the strength distribution were treated as strong opponents, while teams in the bottom quarter were treated as weak opponents.

At first glance, the story seems clear. After beating a strong team, clubs won their next game slightly more often than expected. After losing to a weak team, they performed worse.

The difference after an impressive win was +1.7 percentage points. After a bad loss, it was -3.2 percentage points.

That certainly looks like momentum. But looking like momentum is not the same as proving it.

Then We Controlled for Team Strength

The next step was to account for the factors that already influence the following game. The statistical model controlled for the strength of the team, the strength of its next opponent and whether the next game was at home or away.

Once those factors were included, the apparent momentum effect became much less convincing.

Neither effect reached conventional statistical significance. In other words, the data does not give us strong enough evidence that beating a strong opponent independently boosts the chance of winning the next game, or that losing to a weak opponent independently damages it.

What If We Avoid Labels Like "Strong" and "Weak"?

Any cutoff can be questioned. Why define the top 25% as strong? Why not the top 20% or top third?

So we also tested the idea more generally. Instead of putting teams into categories, we measured how surprising the previous result was relative to expectations.

If momentum is real, an unexpectedly good result should provide useful information about the next game, while an unexpectedly bad result should point in the opposite direction.

Again, the additional effect was not statistically significant: p = 0.271.

Why Fans Can Still Feel Momentum

None of this means that confidence or psychology do not exist. It means something narrower: in this EuroLeague dataset, the previous result did not provide strong additional predictive information once the underlying matchup was taken into account.

There is also a natural selection effect. Strong teams produce more impressive wins because they are strong. Weak teams produce more disappointing losses because they are weak. Without adjusting for that baseline ability, it is easy to credit the previous game for something that may simply be team quality.

What This Means for Prediction

For a prediction model, the lesson is useful. A dramatic result should not automatically receive extra weight simply because it feels important.

Beating an elite opponent may contain new information about a team's current level. Losing to a weaker opponent may also reveal something. But the result needs to be evaluated alongside the team's established strength, the next opponent and the location of the next game.

Otherwise, a model risks turning a compelling basketball narrative into a variable that adds little predictive value.

Momentum or Myth?

Our raw EuroLeague numbers point in the direction basketball fans would expect. Teams performed slightly better after beating strong opponents and slightly worse after losing to weak ones.

But after accounting for the strength of the teams and the next matchup, the evidence was not strong enough to conclude that the previous result creates an independent momentum effect.

Methodology: DunkOnOdds EuroLeague database, seasons 2014-2025. Opponent strength was determined using information available before each game to avoid using future results. Strong opponents were defined as the top quartile of pre-game strength and weak opponents as the bottom quartile. Expected next-game win probability accounts for team strength, opponent strength and home/away status. Results describe historical associations and do not establish causal effects.