Sat, Sep 27 2025
·
Week 5
·
🏟 Stanford Stadium
Stanford, CA
·
Turf
·
50,424 cap
Matchup Prediction
Stanford
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Stanford entering this game.
Momentum Control
58.4%
Stanford wins
Lean
Game Control
50.6%
Stanford wins
Toss-up
Vegas Spread
Stanford -3
O/U 49.5
DraftKings
Advanced Stats
PPA + Success Rate agree → San José State
· 73.9% ATS historically
↓ See full breakdown
San José State 2025 Schedule
San José State's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 8/29 | San José State vs Central Michigan | -11.5L14–16 | 50.5 | L14–16 | U | N |
| Sat 9/6 | San José State at Texas | +37.0L7–38 | 52.5 | L7–38 | U | Y |
| — Bye Week — | ||||||
| Sat 9/20 | San José State vs Idaho | -14.5W31–28 | 51.5 | W31–28 | O | N |
| Sat 9/27 | San José State at Stanford | +3.0L29–30 | 49.5 | L29–30 | O | Y |
| Fri 10/3 | San José State vs New Mexico | -1.5W35–28 | 58.5 | W35–28 | O | Y |
| Sat 10/11 | San José State at Wyoming | -1.5L28–35 | 50.5 | L28–35 | O | N |
| Fri 10/17 | San José State at Utah State | +3.0L25–30 | 63.5 | L25–30 | U | N |
| — Bye Week — | ||||||
| Sat 11/1 | San José State vs Hawai'i | -2.5W45–38 | 55.5 | W45–38 | O | Y |
| Sat 11/8 | San José State vs Air Force | -6.0L16–26 | 67.5 | L16–26 | U | N |
| Sat 11/15 | San José State at Nevada | -10.0L10–55 | 49.5 | L10–55 | O | N |
| Sat 11/22 | San José State at San Diego State | +10.0L3–25 | 50.5 | L3–25 | U | N |
| Sat 11/29 | San José State vs Fresno State | +3.5L14–41 | 46.0 | L14–41 | O | N |
Stanford 2025 Schedule
Stanford's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/23 | Stanford at Hawai'i | +1.5L20–23 | 53.5 | L20–23 | U | N |
| Sat 9/6 | Stanford at BYU | +20.5L3–27 | 44.5 | L3–27 | U | N |
| Sat 9/13 | Stanford vs Boston College | +14.0W30–20 | 44.5 | W30–20 | O | Y |
| Sat 9/20 | Stanford at Virginia | +16.5L20–48 | 48.5 | L20–48 | O | N |
| Sat 9/27 | Stanford vs San José State | -3.0W30–29 | 49.5 | W30–29 | O | N |
| — Bye Week — | ||||||
| Sat 10/11 | Stanford at SMU | +19.5L10–34 | 55.5 | L10–34 | U | N |
| Sat 10/18 | Stanford vs Florida State | +17.5W20–13 | 55.5 | W20–13 | U | Y |
| Sat 10/25 | Stanford at Miami | +28.5L7–42 | 45.5 | L7–42 | O | N |
| Sat 11/1 | Stanford vs Pittsburgh | +13.5L20–35 | 51.5 | L20–35 | O | N |
| Sat 11/8 | Stanford at North Carolina | +8.5L15–20 | 41.5 | L15–20 | U | Y |
| — Bye Week — | ||||||
| Sat 11/22 | Stanford vs California | +4.5W31–10 | 47.5 | W31–10 | U | Y |
| Sat 11/29 | Stanford vs Notre Dame | +32.5L20–49 | 50.5 | L20–49 | O | Y |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2025 season
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
Split
Metrics disagree
Elite · 82.4% ATS
PPA + PPO + Havoc
Split
Metrics disagree
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ San José State
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
PPA Passing
Pass efficiency edge · Strong predictor
Havoc Total
Def. disruption rate · Strong predictor
TFLs, sacks, PBUs, forced fumbles — higher is better
Points Per Opp
Drive-finishing edge · Strong predictor
Success Rate
Play consistency edge · Solid predictor
Field Position
Avg start (lower=better) · Solid predictor
Avg yards from own endzone to average start — lower is better · longer bar = better field position
Advanced stats sourced from CFBD · 2025 season ·
Edges are matchup-adjusted (offense vs opponent defense)
Power Ratings
Team Power Ratings
Overall · Offense · Defense ratings · Updated as season progresses
Power ratings updated throughout the season as results accumulate
Momentum Control (CSS)
Consecutive Scoring Sequences
Who builds scoring momentum?
Stanford Edge
Stanford +0.50
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 4 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Stanford Edge
Stanford +2.5
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 4 games this season
Actual Result
CSS Battle
Tie
1 — 1 sequences
✗ Predicted incorrectly
GC Battle
San José State
24.4 — 57.3 GC score
✗ Predicted incorrectly
Game Result
Stanford won by 1
✓ Model called it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Stanford, but the GC edge is small. When metrics agree but GC is near-neutral, the agreed-upon team has covered only 46.7% of the time historically (n=224) — potentially a fade signal.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
San José State
Ken Niumatalolo #1
7–5 (58%)
· Yr 2 at school
OC
Craig Stutzmann
Yr 2
#1
DC
Derrick Odum
Yr 3
#1
Stanford
Troy Taylor #1
6–18 (25%)
· Yr 3 at school
OC
Troy Taylor
Yr 3
#1
DC
Bobby April
Yr 1
#1
About these metrics
Advanced Stats shows matchup-adjusted factor edges (offense vs opponent defense). Combination signals — when PPA, PPO, Success Rate, and Havoc all point the same direction — have historically predicted the SU winner in 95–97% of games and the ATS winner in 82–83% of games (2021–2025, FBS vs FBS, regular season).
Impact: Advanced Stats are the best performance based metric used to predict the outcome of games. ✓
Momentum Control (CSS) measures consecutive scoring sequences — when a team scores, holds the opponent scoreless, then scores again. Teams entering a game with a CSS edge of +1.0 or more have won 71–78% of games historically (2021–2025, FBS vs FBS).
Impact: Momentum Control is a great measure for predicting game outcome but NOT an ATS advantage, data shows this is already considered when lines are set. ✗
Game Control (GC) measures win probability dominance — how thoroughly a team controlled the game from start to finish. Teams with a GC edge of +12 or more have won 67–76% of games historically. When both metrics agree, combined confidence is higher. When they split, treat as a lean at best.
Impact: Game Control is another great measure for predicting game outcome but NOT an ATS advantage, data shows this is already considered when lines are set. ✗
Power Ratings are a custom-built composite of a Teams Talent, Experience & Production, Coaching & Performance Metrics. These are updated constantly with roster changes, performance once the games start for the 2026 season, injuries the team is dealing with and scheduling situations.
Impact: There are a wide range of power ratings available, we think ours is the best, you can decide for yourself ✓
Advanced Stats shows matchup-adjusted factor edges (offense vs opponent defense). Combination signals — when PPA, PPO, Success Rate, and Havoc all point the same direction — have historically predicted the SU winner in 95–97% of games and the ATS winner in 82–83% of games (2021–2025, FBS vs FBS, regular season).
Impact: Advanced Stats are the best performance based metric used to predict the outcome of games. ✓
Momentum Control (CSS) measures consecutive scoring sequences — when a team scores, holds the opponent scoreless, then scores again. Teams entering a game with a CSS edge of +1.0 or more have won 71–78% of games historically (2021–2025, FBS vs FBS).
Impact: Momentum Control is a great measure for predicting game outcome but NOT an ATS advantage, data shows this is already considered when lines are set. ✗
Game Control (GC) measures win probability dominance — how thoroughly a team controlled the game from start to finish. Teams with a GC edge of +12 or more have won 67–76% of games historically. When both metrics agree, combined confidence is higher. When they split, treat as a lean at best.
Impact: Game Control is another great measure for predicting game outcome but NOT an ATS advantage, data shows this is already considered when lines are set. ✗
Power Ratings are a custom-built composite of a Teams Talent, Experience & Production, Coaching & Performance Metrics. These are updated constantly with roster changes, performance once the games start for the 2026 season, injuries the team is dealing with and scheduling situations.
Impact: There are a wide range of power ratings available, we think ours is the best, you can decide for yourself ✓