Trading NBA games on Polymarket, perhaps you, like many others, have had this experience: before the game, you see one team with a significantly higher win probability than their opponent, only for them to collapse in the fourth quarter and get swept away by a scoring run (like the recent Hornets and Heat game—I lost so much on that bet it made me question my life).
Since everyone says Polymarket is a "truth machine," does that mean I can easily make money by blindly buying the team with the higher pre-game win probability?
To test this hypothesis, I backtested the 1,096 regular-season games of the NBA 2025-26 season. The data revealed the truth—
Blindly following the market won't make you money, but it won't lose you much either; the pre-game probabilities are fully priced in.
Blindly Buying the Market Favorite is a Guaranteed Loss
The backtesting strategy was very simple:
- Used the average probability from 3 minutes before the game as a benchmark
- Traded $100 on each game
- Always bought the side with the "higher win probability"
Results:
- Total amount wagered: $109,600. Total amount returned: $107,545.20. Net loss: $2,054.
- ROI: -1.87%
This shows that Polymarket's prices are quite efficient; the market has fully priced in the teams' win probabilities, leaving no "arbitrage" opportunity.
The difference in ROI likely comes from other dimensions like transaction costs and emotional premiums. If you insist on "buying blindly," you might as well bet against the market—you could even make a 1.87% profit.
The Real Value: Not All Teams Are Created Equal
The above backtest was for the entire set of a thousand games. I then broke it down from multiple angles to try and find parts that break free from the market's gravity:
- By week: Random walk
- By probability: Still a random walk. That is, betting on pre-game win probabilities of 50%, 60%, 70%, or 80% showed no difference in returns.
- By team: Here, clear differences emerged.
Some teams simply live up to the market's trust—
When the market thinks they will win, they are more likely to actually win.
- POR (Trail Blazers): ROI 19%
- PHI (76ers): ROI 14%
- SAS (Spurs): ROI 12%
- LAL (Lakers): ROI 11%
- CHA (Hornets): ROI 9%
Why is there such a difference for these teams? As the author previously had little understanding of NBA teams themselves, an initial hypothesis was formed:
Are they the strongest or the weakest teams, thus having high expectation consistency?
But upon verification, this was not the case. Except for SAS (Spurs), the other four teams were only ranked in the middle to slightly above average positions.
So what about the teams with the best records? The market has already fully priced them in. Blindly buying them yields an average ROI of only 2.16%; the pre-game betting odds contain no水分 (water/hidden value).
- DET (Pistons): ROI 1%
- BOS (Celtics): ROI 4%
- NYK (Knicks): ROI 3%
- OKC (Thunder): ROI -2%
- DEN (Nuggets): ROI -5%
What about the weakest teams?
Here, there is extreme divergence instead. These teams are almost never favored by the market. For example, the Nets (BKN) were only favored (win probability >50%) in 7 games, won 5 of them, resulting in a high ROI of 21%; while the Pacers (IND) were favored in 8 games, won 4, but had an ROI of -20%. The sample size is too small to serve as a trading reference.
This means, theoretically (only theoretically!), POR (Trail Blazers), PHI (76ers), SAS (Spurs), LAL (Lakers), and CHA (Hornets) are the range defined by the existing data for following.
