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Player props and team markets for the next scheduled NBA meeting between the Atlanta Hawks and the Milwaukee Bucks. Every prop the books have posted for this game is scored the same way: the player’s own game log measured against the exact line on offer, then compared with the price after a short record is pulled toward that price, so a hot fortnight cannot pass for a gap over it. The result is an estimate of whether the measured history sits ahead of or behind that price. It is not a claim the sportsbook has it wrong, and it is not a forecast of this game.
Props whose hit rate, pulled toward the price for a short record, sits ahead of the break-even the current price implies, with at least ten games behind the hit rate, a B grade or better, and a price a book has refreshed recently. Most props on most games clear none of that. When none do, the page says so rather than ranking the least-bad options.
Every other prop posted for this game, with the reason it did not clear the bar, a thin sample, a price worse than the measured history, a line no book has refreshed. These are real market data and belong on the page; they are not suggestions.
Moneyline, spread, game total and team totals for this NBA game, at the best posted price, alongside how often each side has landed historically. These carry no grade and no hit-rate-vs-price figure: there is no calibrated team model behind them, so the page shows the numbers and stops.
Whatever the books have priced for this NBA game, the board on this page loads live rather than from a saved snapshot, so it reflects what is actually on offer now. Each prop carries its measured hit rate, the number of games that rate is drawn from, and how the price compares with that history.
Each prop is graded by its measured hit rate at the exact line the book is offering, with the number of games behind the rate shown beside the letter. Separately, the rate is compared with the price after a short record is pulled toward that price, so a short hot streak cannot masquerade as a gap over it. That is history, not a forecast, and not a claim that the sportsbook has the price wrong.
Only those whose hit rate, pulled toward the price for a short record, sits ahead of the break-even that price implies, with at least ten games behind the hit rate, a B grade or better, and a price a book has refreshed recently. Most props on any given game clear none of that, and when none do this page says so instead of filling the space with the least-bad options.
No. Every figure here is measured history against a current price, and history is not a forecast. Across roughly 96,000 graded props the model tracked the de-vigged consensus across five books to within the margin those books charge: historical testing showed calibration alone is not enough to overcome sportsbook pricing. What this page does is show you the sample behind every number in seconds.
Moneyline, spread, game total and team totals, at the best price posted, with how often each side has landed historically. They carry no grade and no hit-rate-vs-price figure, because there is no calibrated team model behind them, so this section shows prices and measured history and stops short of rating them.
Estimate from measured history against this price, after shrinking for sample size. Not a forecast.
Past performance does not predict future results. Every figure here is history and estimate, not a forecast of what will happen.
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New to the numbers on this page? Two short explainers: how to read a hit rate and what its denominator hides, what an over/under line is and what it is not.
12 players in this game carry a posted prop and enough logged history to measure: 6 for the Atlanta Hawks and 6 for the Milwaukee Bucks. The averages below are counted from official box scores and rebuilt daily; the lines and prices for this game load live above, because they move through the day.
| Player | Deepest market | Logged games | Average | At a balanced line |
|---|---|---|---|---|
| Nickeil Alexander-Walker | Points + Rebounds + Assists | 97 | 27.3 combined points, rebounds and assists | 46 of 97 over 26.5 (47%) |
| Luguentz Dort | 3-Pointers Made | 97 | 1.8 three-pointers | 47 of 97 over 1.5 (48%) |
| Dyson Daniels | Points | 95 | 11.3 points | 53 of 95 over 10.5 (56%) |
| Onyeka Okongwu | 3-Pointers Made | 93 | 1.9 three-pointers | 54 of 93 over 1.5 (58%) |
| Aaron Wiggins | 3-Pointers Made | 91 | 1.5 three-pointers | 36 of 91 over 1.5 (40%) |
| Jalen Johnson | Points | 88 | 22.0 points | 44 of 88 over 21.5 (50%) |
| Player | Deepest market | Logged games | Average | At a balanced line |
|---|---|---|---|---|
| Ryan Rollins | 3-Pointers Made | 87 | 2.4 three-pointers | 35 of 87 over 2.5 (40%) |
| Myles Turner | Rebounds | 83 | 5.4 rebounds | 37 of 83 over 5.5 (45%) |
| Kyle Kuzma | Points | 82 | 12.7 points | 42 of 82 over 12.5 (51%) |
| Tyler Herro | Points | 46 | 20.8 points | 23 of 46 over 21.5 (50%) |
| Brayden Burries | 3-Pointers Made | 13 | 0.8 three-pointers | 10 of 13 over 0.5 (77%) |
| Nate Ament | Rebounds | 11 | 2.6 rebounds | 6 of 11 over 2.5 (55%) |
Both clubs' own NBA record, counted from official box scores through 2026-11-13 rather than from anything posted for this game, so a club whose season has ended is showing that season. The Atlanta Hawks have won 55 of 101 logged games at 117.3 points a game; the Milwaukee Bucks have won 33 of 95 at 110.0. These are records, not a forecast of this game, and neither column carries a price, a line or a grade.
| Measure | Atlanta Hawks | Milwaukee Bucks |
|---|---|---|
| Logged games in this window | 101 | 95 |
| Games won | 55 of 101 | 33 of 95 |
| Points scored per game | 117.3 | 110.0 |
| At home | 28 of 50 won, 116.9 per game | 20 of 48 won, 113.4 per game |
| Away | 27 of 51 won, 117.7 per game | 13 of 47 won, 106.6 per game |
| Last 10 games | 116.2 per game | 102.3 per game |
| Last 5 games | 122.8 per game | 100.0 per game |
| Highest and lowest score logged | 150 and 86 | 147 and 79 |
| Counted through | 2026-11-13 | 2026-11-13 |
How NBA prop markets behave, measured across the league
Odds and lines come from licensed data feeds and refresh on a schedule; hit rates and grades are Parlay Builder’s own calculations.