Hit rate · Week 9
Player Prop Hit Rates
How many of his games have cleared each line, for every player in this week's qualifying population — with the line a book is offering, the price with the vig taken out, and the games behind the count. Counted from game logs, with the weeks named so you can check them. No projections, and no picks.
927 pages over 450 players · counts Nov 3, 6:01 PM EST · prices Nov 3, 6:01 PM EST
Player props · Week 9
| Market | Opp | Line | At that line | De-vig | Slip | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Adonai Mitchell NYJ WR | receiving yards | @ KC30 | o 35.5 | 3 of 475.0% | −116bet365 | 50.0% | 6.9% | — | — | 1 | ||
| Amon-Ra St. Brown DET WR | receiving yards | @ MIA29 | o 81.5 | 2 of 728.6% | −116bet365 | 50.0% | 6.9% | — | — | 1 | ||
| Brian Thomas Jr. JAX WRPRICED | receiving yards | @ BAL5 | o 10.5 | 4 of 757.1% | −112 | 50.0% | 5.4% | 2.98u | +1.0ppFA | 9 | ||
| Caleb Douglas MIA WR | receiving yards | vs DET6 | o 37.5 | 3 of 475.0% | −116bet365 | 50.0% | 6.9% | — | — | 1 | ||
| CeeDee Lamb DAL WR | receiving yards | @ IND23 | o 84.5 | 3 of 837.5% | −116bet365 | 50.0% | 6.9% | — | — | 1 | ||
| Chris Olave NO WR | receiving yards | vs CLE20 | o 75.5 | 4 of 757.1% | −116bet365 | 50.0% | 6.9% | — | — | 1 | ||
| Christian Watson GB WR | receiving yards | @ NE10 | o 72.5 | 4 of 850.0% | −112 | 50.0% | 5.4% | 2.98u | +0.8ppBE | 6 | ||
| Courtland Sutton DEN WR | receiving yards | @ CAR16 | o 35.5 | 3 of 837.5% | −110 | 49.6% | 5.3% | 1.17u | +0.5ppCA | 5 | ||
| Darnell Mooney NYG WR | receiving yards | @ PHI4 | o 12.5 | 4 of 757.1% | −116bet365 | 50.0% | 6.9% | — | — | 1 | ||
| Denzel Boston CLE WR | receiving yards | @ NO17 | o 46.5 | 3 of 837.5% | −116bet365 | 50.0% | 6.9% | — | — | 1 | ||
| Devaughn Vele NO WR | receiving yards | vs CLE20 | o 44.5 | 4 of 757.1% | −116bet365 | 50.0% | 6.9% | — | — | 1 | ||
| DJ Moore BUF WR | receiving yards | @ MIN27 | o 39.5 | 3 of 560.0% | −125bet365 | 50.8% | 8.5% | — | — | 1 | ||
| Dohnte Meyers CIN WRPRICED | receiving yards | @ ATL15 | o 16.5 | 4 of 757.1% | −114 | 50.0% | 6.1% | 0.38u | +1.0ppES | 4 | ||
| Drake London ATL WR | receiving yards | vs CIN18 | o 77.5 | 3 of 837.5% | −114 | 50.4% | 5.3% | 2.98u | +0.4ppDR | 5 | ||
| Emeka Egbuka TB WR | receiving yards | @ CHI13 | o 46.5 | 3 of 650.0% | −113DraftKings | 50.2% | 5.4% | — | — | 1 | ||
| Garrett Wilson NYJ WR | receiving yards | @ KC30 | o 52.5 | 5 of 862.5% | −116bet365 | 50.0% | 6.9% | — | — | 1 | ||
| Ja'Kobi Lane BAL WR | receiving yards | vs JAX1 | o 15.5 | 2 of 450.0% | −112 | 50.0% | 5.4% | 2.98u | +1.0ppFA | 10 | ||
| Ja'Marr Chase CIN WR | receiving yards | @ ATL15 | o 78.5 | 2 of 728.6% | −110 | 49.6% | 5.3% | 1.17u | −0.4ppDR | 2 | ||
| Jahan Dotson ATL WR | receiving yards | vs CIN18 | o 26.5 | 4 of 850.0% | −114 | 50.4% | 5.3% | 2.98u | −0.7ppBE | 7 | ||
| Jakobi Meyers JAX WR | receiving yards | @ BAL5 | o 40.5 | 2 of 728.6% | −110 | 49.6% | 5.3% | 1.17u | −1.0ppFA | 7 | ||
| Jalen Coker CAR WR | receiving yards | vs DEN24 | o 52.5 | 3 of 650.0% | −113 | 50.2% | 5.4% | 1.17u | +0.2ppDR | 3 | ||
| Jalen Royals KC WRPRICED | receiving yards | vs NYJ28 | o 2.5 | 4 of 757.1% | −116bet365 | 50.0% | 6.9% | — | — | 1 | ||
| Jameson Williams DET WR | receiving yards | @ MIA29 | o 53.5 | 3 of 742.9% | −116bet365 | 50.0% | 6.9% | — | — | 1 | ||
| Jaylen Waddle DEN WR | receiving yards | @ CAR16 | o 43.5 | 2 of 825.0% | −111 | 49.8% | 5.4% | 3.82u | +0.5ppCA | 7 | ||
| Jordan Addison MIN WR | receiving yards | vs BUF9 | o 39.5 | 3 of 650.0% | −116bet365 | 50.0% | 6.9% | — | — | 1 |
No edge column, no value badge, no projection — and no sort by any of them. Hit count and the book's de-vig have different denominators and are never subtracted. The two comparison columns are prices against prices at one line: Spread is what choosing the dearest book instead of the cheapest costs you, and Outlier is how far one book sits from the median of the others — a fact about the books, not a view on which side wins. Hold is the only coloured number, because it is a cost rather than a judgement. Pick'em operators and exchanges are excluded by name.
What this board will not tell you
Which side to bet. These are counts, not forecasts. A hit probability was built and measured — it beat the positional base rate by 5.4% of log loss — and it is not shown, because the pre-registered rule required calibration at every rung as well and the worst rung missed it. So this panel shows what he actually did, which needs no model.
Read the count column down the page and it hugs half his games, because a book moves its line until it does — study:props-market measured within-cell resolution of 0.0033 and a mean de-vigged fair price of 48.9–49.8% across all six markets. That is the finding, not a gap to act on. The trend column is where the information actually is: it is the same count, unpacked into the games it came from.
Prices from SportsGameOdds player props, two-way sportsbooks only. Pick'em operators and exchanges are excluded by name and with the measured reason — a pick'em quotes both sides at even money, so its hold computes to exactly 0.00% and it would rank first in any table ordered by hold without being the cheapest way to make the bet. Open a player for the full ladder, a line you can move, and every book on it.
The player lookup has his injury row, his game's forecast and the rest of his markets.