Basketball is supposed to be the sport where the better team almost always wins — no flukey bounces, no goalie standing on his head, just talent grinding out over 48 minutes. The 2023-24 data mostly agrees, with one big asterisk: the better team won 67.9% of games across the season, but that headline hides a steep gradient. In a toss-up, the favorite barely cleared a coin flip (55%); in a true mismatch, it won four times out of five (81%). How deterministic the NBA is depends entirely on how far apart the two teams are.

How I defined "the better team"

For every game I labeled the “better team” as the one with the higher season net rating — points scored minus allowed per 100 possessions, the cleanest one-number measure of team quality. Then I took the gap between the two teams’ net ratings, bucketed every game by how big that gap was, and asked: how often did the higher-rated team actually win? That turns a vague question (“does the better team win?”) into a measurable one (“the better team wins X% of the time when it’s this much better”).

The exhibit: predictability rises with the gap

A bar chart showing the share of 2023-24 NBA games the better team (by season net rating) won, split by the size of the net-rating gap. Toss-ups under 2 points: 55%. Slight edges of 2 to 5: 58%. Clear edges of 5 to 8: 71%. Mismatches of 8-plus: 81%. A dashed line marks the 50% coin-flip level. The title notes 67.9% overall.
Share of 2023-24 games won by the higher-net-rating team, by the size of the pre-game rating gap. From a near-coin-flip in toss-ups to 81% in mismatches — the better team’s edge grows steadily with the talent gap. Data: 2023-24 NBA games + team net ratings (Basketball-Reference).

The staircase is the whole story. When two teams are within 2 points of net rating — genuinely matched — the “better” team won just 55%, barely better than chance. A slight edge (2–5) bumped it to 58%. A clear edge (5–8) jumped to 71%. And in mismatches of 8-plus points per 100 — a contender hosting a tanker — the favorite won 81% of the time. The NBA is highly predictable, but only when the teams are actually unequal; among peers, it’s nearly a coin flip.

55% → 81% How often the better team won, from toss-ups (net-rating gap under 2) to mismatches (8+). Predictability is a function of the talent gap, not a constant.

Why 68% is high — and why it isn't higher

Compare that 67.9% to other sports and the NBA’s reputation holds up. Favorites win far more often in basketball than in, say, baseball or soccer, where a single game is dominated by variance and the better team might win 55–60% at most. Five-on-five over 100-plus possessions gives talent a lot of room to express itself; the law of large numbers works inside a single game.

So why doesn’t the better team win 80%+ across the board? Because most NBA games aren’t mismatches. The leaguewide 68% is a blend dominated by the many close-matchup games sitting near a coin flip, dragged up by the minority of blow(out)-prone mismatches. The single number is real but misleading on its own — it’s the average of a 55% world and an 81% world, and which one you’re watching depends on the marquee.

A worked example: reading a single matchup

Say the Celtics (net rating around +11 in 2023-24) host a roughly average team (net rating near 0). That’s an 11-point gap — deep into the mismatch bucket — so the model says Boston wins about 81% of the time, before you even add home court. Now put two +3 and +1 teams together: a 2-point gap, the toss-up bucket, and the “better” team is only about 55% to win. Same league, same night, wildly different certainty. This is why “the better team always wins in the NBA” is true for the Celtics-versus-cellar game and basically false for two playoff-caliber teams trading blows.

Where this read has limits

  • It’s in-sample. I used full-season net ratings to label games within that same season — the ratings already “know” how the games turned out. A true pre-game forecast (using only prior information) would be a little less accurate, so treat these as upper-ish bounds on predictability, not live betting numbers.
  • Net rating isn’t destiny. A season-long average smooths over injuries, trades, rest, and schedule fatigue — the team that was +11 over the year might be +3 tonight with two starters out. The gap is a strong proxy, not the exact matchup truth.
  • No home court in the buckets. I labeled the favorite purely by rating, ignoring venue. Home advantage would lift the home favorite’s number and cut the road favorite’s; folding it in is the natural next step (see home-court advantage).
  • One season. 1,200-odd games is plenty to see the gradient, but the exact percentages will wobble year to year; the shape — rising with the gap — is the robust part.

The takeaway

“Does the better team win?” has a satisfying NBA answer: usually — 68% of the time — and much more than usually when the teams are far apart. But the honest version replaces the single number with a gradient. The favorite is a near coin flip among equals and a near lock in a mismatch, and almost every interesting game in the league lives somewhere on that slope. Predictability isn’t a fixed property of the sport; it’s a function of how unequal tonight’s two teams happen to be.

Reproduce it

Join each game in data_layer/nba_home_results.csv to the two teams’ net ratings in data_layer/nba_ratings.csv, label the higher-rated team the favorite, bucket by the absolute rating gap, and compute the favorite’s win rate in each bucket. The chart is regenerated by charts/chart_better_team_win_rate.py — no network, nothing hand-entered.

Sources & Further Reading

C. B. Zakarian

C. B. Zakarian writes NBAAnalytic, an independent basketball-analytics site. He builds the ratings, models, and charts here from public data, and would rather show the working than hand down a hot take. More about the methodology →