Can You Make a Steady Profit by Blindly Following Polymarket's Pre-Game Win Probability to Bet on NBA Games?

marsbitОпубліковано о 2026-04-17Востаннє оновлено о 2026-04-17

Анотація

The article investigates whether blindly betting on NBA teams with higher pre-game win probabilities on Polymarket guarantees profits. Backtesting data from the 2025-26 regular season (1,096 games) shows that a strategy of consistently betting $100 on the team with the higher pre-game probability resulted in a net loss of $2,054 (ROI: -1.87%), indicating that the market is efficient and prices are accurately set. Further analysis reveals that returns varied significantly by team. Certain teams, such as the Trail Blazers (POR, 19% ROI), 76ers (PHI, 14%), Spurs (SAS, 12%), Lakers (LAL, 11%), and Hornets (CHA, 9%), consistently outperformed market expectations when favored. In contrast, top-performing teams like the Celtics, Knicks, and Nugks had ROIs close to zero or negative, showing their probabilities were efficiently priced. The weakest teams showed extreme ROI variations but had insufficient sample sizes for reliable conclusions. The key takeaway is that blindly following pre-game probabilities is not a profitable strategy overall, but targeting specific teams may yield better results.

When trading NBA games on Polymarket, perhaps you, like many others, have had this experience: before the game, you see one team's win probability is significantly higher than their opponent's, only for them to collapse in the fourth quarter and get swept away (like the recent Hornets and Heat game—I lost so much on that bet I started questioning my life).

Since everyone says Polymarket is a "truth machine," does that mean I can just blindly bet on the team with the higher pre-game win probability and easily make money?

To test this hypothesis, I backtested the 1,096 regular-season games of the NBA 2025-26 season. The data reveals the truth—

Blindly following the market won't make you money, but you won't lose much either; the pre-game probabilities are fully priced in.

Blindly Buying with the Market Guarantees a Loss

The backtesting strategy was very simple:

Used the average probability from 3 minutes before the game as a benchmark
Traded $100 per game
Always bought the side with the "higher win probability"

Results:

Total amount spent: $109,600; total amount returned: $107,545.2; 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; that would yield a 1.87% profit.

The Real Value: Not All Teams Are Created Equal

The above backtest was for the overall sample 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%, versus 70%, 80% showed no difference in returns.
By team: Here, clear differences emerged.

Some teams 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 do these teams show such differences? As the author previously had little knowledge of NBA teams, I first had a hypothesis:

Are they the strongest or the weakest teams, thus having high expectation consistency?

But upon checking, the facts proved otherwise. Except for SAS (Spurs), the other four teams are only ranked in the middle to slightly above average positions.

What about the teams with the best records? Actually, the market has already fully priced them in. The average ROI from blindly buying their higher probability is only 2.16%; the pre-game betting probabilities contain no水分 (water).

DET (Pistons): ROI 1%
BOS (Celtics): ROI 4%
NYK (Knicks): ROI 3%
OKC (Thunder): ROI -2%
DEN (Nuggets): ROI -5%

What about the weakest?

Here, there's extreme divergence. These teams hardly ever have games where the market favors them to win. For example, the Nets (BKN) only had 7 games with a win probability greater than 50%, won 5 of them, resulting in an ROI of 21%; whereas the Pacers (IND) had only 8 games greater than 50%, 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划定 (delineated) by the existing data for following.

Пов'язані питання

QAccording to the article, what was the overall ROI of blindly following the higher pre-game win probability on Polymarket for NBA games?

AThe overall ROI was -1.87%, meaning a loss of $2,054 on a total investment of $109,600.

QWhich NBA team had the highest positive ROI when blindly backing them as the pre-game favorite on Polymarket?

AThe Portland Trail Blazers (POR) had the highest positive ROI at 19%.

QWhat was the article's conclusion about the efficiency of the Polymarket's pricing for NBA games?

AThe article concluded that the market is quite efficient, with pre-game probabilities being fully priced, leaving no arbitrage opportunity for a simple 'blind buying' strategy.

QDid the article find a significant difference in ROI when betting on teams with different pre-game probability brackets (e.g., 50% vs 80%)?

ANo, the article found that the ROI was essentially a random walk across different probability brackets, showing no significant difference in returns.

QAccording to the author's test, what would have been the result of always betting against the pre-game favorite instead of with it?

ABetting against the pre-game favorite would have resulted in a positive ROI of 1.87%.

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