Pre-game prop analysis powered by recent player performance. Every prop graded before tipoff.
| # | Sport | Player | Matchup | Stat | Line | Odds | L5 Avg | Edge | Hit | Trend | Score | Grade | Final | Over | Under | Books |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 601 | MLB | Dylan Crews 10 games | WSH vs WSN@SFG | H | 0.5 | -165 | 0.6 | +0.1 | 2/5 | -0.1 | 33 | F | 0.0 | LOSS | WIN | |
| 602 | MLB | George Springer 10 games | TOR vs PHI@TOR | H | 0.5 | -190 | 0.6 | +0.1 | 2/5 | -0.2 | 33 | F | 0.0 | LOSS | WIN | |
| 603 | MLB | James Wood 10 games | WSH vs WSN@SFG | H | 0.5 | -180 | 0.6 | +0.1 | 2/5 | +0.3 | 33 | F | 1.0 | WIN | LOSS | |
| 604 | MLB | Masataka Yoshida 10 games | BOS vs BOS@TBR | H | 0.5 | -211 | 0.6 | +0.1 | 2/5 | -0.4 | 33 | F | — | PENDING | PENDING | |
| 605 | MLB | Sal Frelick 10 games | MIL vs MIL@Athlet | H | 0.5 | -210 | 0.6 | +0.1 | 2/5 | -0.1 | 33 | F | 0.0 | LOSS | WIN | |
| 606 | MLB | Sal Stewart 10 games | CIN vs CIN@SDP | H | 0.5 | -200 | 0.6 | +0.1 | 2/5 | -0.2 | 33 | F | 1.0 | WIN | LOSS | |
| 607 | MLB | Ty France 10 games | SD vs CIN@SDP | H | 0.5 | -190 | 0.6 | +0.1 | 2/5 | -0.4 | 33 | F | 1.0 | WIN | LOSS | |
| 608 | MLB | Willy Adames 10 games | SF vs WSN@SFG | H | 0.5 | -180 | 0.8 | +0.3 | 2/5 | -0.2 | 33 | F | 0.0 | LOSS | WIN | |
| 609 | NBA | Luke Kornet 10 games | SAS vs NYK | REB | 2.50 | +125 | 2.8 | +0.3 | 3/5 | -0.7 | 32 | F | 5.0 | WIN | LOSS | |
| 610 | MLB | Adley Rutschman 10 games | BAL vs SEA@BAL | HR | 0.5 | +600 | 0.2 | -0.3 | 1/5 | +0.2 | 32 | F | — | PENDING | PENDING | |
| 611 | MLB | Adolis Garcia 6 games | PHI vs PHI@TOR | HR | 0.5 | +500 | 0.2 | -0.3 | 1/5 | +0.2 | 32 | F | — | PENDING | PENDING | |
| 612 | MLB | Adolis Garcia 6 games | PHI vs PHI@TOR | TB | 1.5 | +150 | 1 | -0.5 | 1/5 | +0.3 | 32 | F | — | PENDING | PENDING | |
| 613 | MLB | Alec Bohm 10 games | PHI vs PHI@TOR | HR | 0.5 | +650 | 0.2 | -0.3 | 1/5 | +0.1 | 32 | F | 0.0 | LOSS | WIN | |
| 614 | MLB | Alika Williams 8 games | ATH vs MIL@Athlet | R | 1.5 | +1000 | 0.6 | -0.9 | 0/5 | +0.6 | 32 | F | 0.0 | LOSS | WIN | |
| 615 | MLB | Alika Williams 8 games | ATH vs MIL@Athlet | RBI | 0.5 | +230 | 0.2 | -0.3 | 1/5 | +0.1 | 32 | F | 1.0 | WIN | LOSS | |
| 616 | MLB | Andrew Vaughn 10 games | MIL vs MIL@Athlet | TB | 2.5 | +170 | 1.4 | -1.1 | 1/5 | +0.9 | 32 | F | 9.0 | WIN | LOSS | |
| 617 | MLB | Andruw Monasterio 10 games | BOS vs BOS@TBR | HR | 0.5 | +750 | 0.2 | -0.3 | 1/5 | +0.2 | 32 | F | 0.0 | LOSS | WIN | |
| 618 | MLB | Andruw Monasterio 10 games | BOS vs BOS@TBR | RBI | 0.5 | +253 | 0.2 | -0.3 | 1/5 | +0.1 | 32 | F | 0.0 | LOSS | WIN | |
| 619 | MLB | Ben Rice 10 games | NYY vs NYY@CLE | HR | 0.5 | +300 | 0.2 | -0.3 | 1/5 | +0.1 | 32 | F | 0.0 | LOSS | WIN | |
| 620 | MLB | Ben Williamson 10 games | TB vs BOS@TBR | R | 0.5 | +200 | 0.2 | -0.3 | 1/5 | +0 | 32 | F | 0.0 | LOSS | WIN | |
| 621 | MLB | Ben Williamson 10 games | TB vs BOS@TBR | RBI | 1.5 | +900 | 0.6 | -0.9 | 1/5 | -0.5 | 32 | F | 0.0 | LOSS | WIN | |
| 622 | MLB | Blake Dunn 10 games | CIN vs CIN@SDP | HR | 0.5 | +1000 | 0.2 | -0.3 | 1/5 | -0.1 | 32 | F | 0.0 | LOSS | WIN | |
| 623 | MLB | Blake Dunn 10 games | CIN vs CIN@SDP | RBI | 1.5 | +900 | 0.6 | -0.9 | 1/5 | -0.3 | 32 | F | 0.0 | LOSS | WIN | |
| 624 | MLB | Blake Perkins 10 games | MIL vs MIL@Athlet | RBI | 0.5 | +200 | 0.2 | -0.3 | 1/5 | +0.2 | 32 | F | 0.0 | LOSS | WIN | |
| 625 | MLB | Brandon Valenzuela 10 games | TOR vs PHI@TOR | R | 1.5 | +2000 | 0.8 | -0.7 | 0/5 | +0.5 | 32 | F | 0.0 | LOSS | WIN | |
| 626 | MLB | Brayan Rocchio 10 games | CLE vs NYY@CLE | HR | 0.5 | +1000 | 0.2 | -0.3 | 1/5 | +0.2 | 32 | F | 0.0 | LOSS | WIN | |
| 627 | MLB | Brayan Rocchio 10 games | CLE vs NYY@CLE | R | 0.5 | +180 | 0.2 | -0.3 | 1/5 | +0 | 32 | F | 0.0 | LOSS | WIN | |
| 628 | MLB | Brayan Rocchio 10 games | CLE vs NYY@CLE | RBI | 0.5 | +262 | 0.2 | -0.3 | 1/5 | +0.1 | 32 | F | 1.0 | WIN | LOSS | |
| 629 | MLB | Brent Rooker 10 games | ATH vs MIL@Athlet | H | 1.5 | +300 | 1 | -0.5 | 1/5 | +0.4 | 32 | F | 0.0 | LOSS | WIN | |
| 630 | MLB | Brice Turang 10 games | MIL vs MIL@Athlet | HR | 0.5 | +550 | 0.4 | -0.1 | 1/5 | +0.5 | 32 | F | 1.0 | WIN | LOSS | |
| 631 | MLB | Bryce Eldridge 10 games | SF vs WSN@SFG | RBI | 0.5 | +185 | 0.2 | -0.3 | 1/5 | -0.4 | 32 | F | 1.0 | WIN | LOSS | |
| 632 | MLB | Bryce Harper 10 games | PHI vs PHI@TOR | RBI | 0.5 | +172 | 0.2 | -0.3 | 1/5 | -0.1 | 32 | F | 0.0 | LOSS | WIN | |
| 633 | MLB | Bryson Stott 10 games | PHI vs PHI@TOR | H | 1.5 | +300 | 0.8 | -0.7 | 1/5 | -0.2 | 32 | F | 1.0 | LOSS | WIN | |
| 634 | MLB | Bryson Stott 10 games | PHI vs PHI@TOR | R | 0.5 | +160 | 0.2 | -0.3 | 1/5 | -0.2 | 32 | F | 1.0 | WIN | LOSS | |
| 635 | MLB | Caleb Durbin 10 games | BOS vs BOS@TBR | H | 1.5 | +320 | 1 | -0.5 | 1/5 | -0.4 | 32 | F | 0.0 | LOSS | WIN | |
| 636 | MLB | Caleb Durbin 10 games | BOS vs BOS@TBR | R | 0.5 | +180 | 0.4 | -0.1 | 1/5 | -0.3 | 32 | F | 0.0 | LOSS | WIN | |
| 637 | MLB | Ceddanne Rafaela 10 games | BOS vs BOS@TBR | RBI | 0.5 | +204 | 0.2 | -0.3 | 1/5 | -0.4 | 32 | F | 0.0 | LOSS | WIN | |
| 638 | MLB | Charles McAdoo 3 games | TOR vs PHI@TOR | HR | 0.5 | +1000 | 0.3 | -0.2 | 1/3 | +0 | 32 | F | — | PENDING | PENDING | |
| 639 | MLB | Charles McAdoo 3 games | TOR vs PHI@TOR | RBI | 1.5 | +1000 | 1 | -0.5 | 1/3 | +0 | 32 | F | — | PENDING | PENDING | |
| 640 | MLB | Chase DeLauter 10 games | CLE vs NYY@CLE | H | 1.5 | +280 | 0.6 | -0.9 | 1/5 | +0 | 32 | F | 1.0 | LOSS | WIN | |
| 641 | MLB | Chase DeLauter 10 games | CLE vs NYY@CLE | R | 0.5 | +140 | 0.2 | -0.3 | 1/5 | +0 | 32 | F | 0.0 | LOSS | WIN | |
| 642 | MLB | Chase DeLauter 10 games | CLE vs NYY@CLE | RBI | 0.5 | +187 | 0.2 | -0.3 | 1/5 | +0 | 32 | F | 0.0 | LOSS | WIN | |
| 643 | MLB | Chase DeLauter 10 games | CLE vs NYY@CLE | TB | 1.5 | +140 | 0.6 | -0.9 | 1/5 | +0 | 32 | F | 1.0 | LOSS | WIN | |
| 644 | MLB | Christian Walker 10 games | HOU vs HOU@LAA | H | 1.5 | +240 | 1 | -0.5 | 1/5 | +0.2 | 32 | F | 2.0 | WIN | LOSS | |
| 645 | MLB | Christian Yelich 10 games | MIL vs MIL@Athlet | RBI | 0.5 | +150 | 0.4 | -0.1 | 1/5 | -0.5 | 32 | F | 0.0 | LOSS | WIN | |
| 646 | MLB | CJ Abrams 10 games | WSH vs WSN@SFG | H | 1.5 | +260 | 0.8 | -0.7 | 1/5 | +0 | 32 | F | 2.0 | WIN | LOSS | |
| 647 | MLB | CJ Abrams 10 games | WSH vs WSN@SFG | R | 1.5 | +1000 | 0.8 | -0.7 | 1/5 | +0.3 | 32 | F | 1.0 | LOSS | WIN | |
| 648 | MLB | Coby Mayo 10 games | BAL vs SEA@BAL | R | 1.5 | +1300 | 0.8 | -0.7 | 1/5 | +0.1 | 32 | F | 1.0 | LOSS | WIN | |
| 649 | MLB | Cody Bellinger 10 games | NYY vs NYY@CLE | HR | 0.5 | +500 | 0.2 | -0.3 | 1/5 | +0.1 | 32 | F | 0.0 | LOSS | WIN | |
| 650 | MLB | Cody Bellinger 10 games | NYY vs NYY@CLE | R | 0.5 | +140 | 0.2 | -0.3 | 1/5 | -0.2 | 32 | F | 0.0 | LOSS | WIN |
Every prop scored on a 0–100 scale before tipoff — built to separate high-confidence plays from coin flips.
The Prop Grader analyzes every available player prop before games begin. It pulls recent performance data — the last 5 to 10 games — and runs each prop through a multi-factor scoring model. The result is a composite score and letter grade that tells you how confident the data is behind any given prop.
Scoring Factors
Edge vs Line (up to 35 pts) — How far the player's recent average sits above or below the prop line. A large positive edge means the player has been consistently clearing this number.
Hit Rate (up to 25 pts) — Out of the last 5 games, how many times did the player actually beat this line? A 5/5 hit rate earns full marks.
Trend (up to 15 pts) — Is the player trending up or down? Compares the last 3 games against the last 10 to detect momentum shifts.
Role Stability (up to 15 pts) — For NBA, this checks minutes consistency. A starter playing 34+ minutes with low variance is more predictable than someone fluctuating between 20 and 35.
Odds Value (up to 10 pts) — Props with plus-money or short juice are more valuable than heavily juiced lines. Better odds mean better expected value.
Grade Scale
A (85–100) — Elite. Strong edge, near-perfect hit rate, positive trend, stable role. These are the highest-confidence props on the board.
B (75–84) — Strong. Most factors are favorable. Solid plays with data backing them up.
C (65–74) — Average. The numbers lean positive but there may be a weak factor pulling the score down.
D (55–64) — Below average. The edge is thin or the recent track record is inconsistent.
F (below 55) — Weak. The data doesn't support this prop. Proceed with caution or skip entirely.
Grades are computed before tipoff using data available at that time. After games complete, each prop is matched against the actual box score and marked as a win, loss, or push.