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Player props and team markets for the next scheduled NFL meeting between the Indianapolis Colts and the Pittsburgh Steelers. 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, shrunk toward a league prior so a hot fortnight cannot pass for an edge, then compared with the price. 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 with a positive shrunk estimate at the current price, 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 NFL game, at the best posted price, alongside how often each side has landed historically. These carry no grade and no edge estimate: there is no calibrated team model behind them, so the page shows the numbers and stops.
Whatever the books have priced for this NFL 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 measured against the exact line the book is offering, then shrunk toward a league prior so a short hot streak cannot masquerade as an edge. What comes out is an estimate of how the measured history compares with the price, research, not a guarantee, and not a claim that the sportsbook has the price wrong.
Only those with a positive shrunk estimate, 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 edge estimate, 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. Research, not a guarantee.
Past performance does not predict future results. Every figure here is history and estimate, not a forecast of what will happen.
No locks. No guaranteed wins. Just market transparency and automated historical parsing.
Parlay Builder is a research and analytics tool. We do not accept wagers, hold funds, or settle bets, and nothing here is a recommendation to place one.
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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.
9 players in this game carry a posted prop and enough logged history to measure — 5 for the Pittsburgh Steelers and 4 for the Indianapolis Colts. 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 |
|---|---|---|---|---|
| Aaron Rodgers | Interceptions | 21 | 0.6 interceptions | 8 of 21 over 0.5 (38%) |
| DK Metcalf | Receptions | 20 | 3.9 receptions | 11 of 20 over 3.5 (55%) |
| Pat Freiermuth | Receptions | 20 | 2.8 receptions | 14 of 20 over 2.5 (70%) |
| Darnell Washington | Receptions | 17 | 2.4 receptions | 9 of 17 over 2.5 (53%) |
| Roman Wilson | Receiving Yards | 13 | 27.2 receiving yards | 6 of 13 over 17.5 (46%) |
| Player | Deepest market | Logged games | Average | At a balanced line |
|---|---|---|---|---|
| Jonathan Taylor | Rush Attempts | 21 | 19.5 carries | 11 of 21 over 18.5 (52%) |
| Tyler Warren | Receptions | 21 | 4.7 receptions | 11 of 21 over 4.5 (52%) |
| Josh Downs | Receptions | 20 | 3.8 receptions | 10 of 20 over 3.5 (50%) |
| Daniel Jones | Interceptions | 17 | 0.7 interceptions | 9 of 17 over 0.5 (53%) |
Both clubs' own NFL record, counted from official box scores through 2026-10-04 rather than from anything posted for this game — so a club whose season has ended is showing that season. The Indianapolis Colts have won 10 of 21 logged games at 27.0 points a game; the Pittsburgh Steelers have won 12 of 22 at 21.8. These are records, not a forecast of this game, and neither column carries a price, a line or a grade.
| Measure | Indianapolis Colts | Pittsburgh Steelers |
|---|---|---|
| Logged games in this window | 21 | 22 |
| Games won | 10 of 21 | 12 of 22 |
| Points scored per game | 27.0 | 21.8 |
| At home | 7 of 11 won, 27.6 per game | 8 of 12 won, 22.3 per game |
| Away | 3 of 10 won, 26.4 per game | 4 of 10 won, 21.3 per game |
| Last 10 games | 22.7 per game | 19.9 per game |
| Last 5 games | 26.4 per game | 16.6 per game |
| Highest and lowest score logged | 41 and 16 | 34 and 3 |
| Counted through | 2026-10-04 | 2026-10-02 |
How NFL prop markets behave, measured across the league
Odds and lines come from licensed data feeds and refresh on a schedule; hit rates, edges and grades are Parlay Builder’s own calculations.