Sun, Sep 3 2023
·
Week 1
·
🏟 LaVell Edwards Stadium
Provo, UT
·
Turf
·
63,725 cap
Sam Houston✈ 1,118 mi-1 hr TZ
Matchup Prediction
Toss-up — no clear edge
Neither metric shows a meaningful pre-game edge in this matchup.
Momentum Control
58.4%
—
Lean
Game Control
50.6%
—
Toss-up
Vegas Spread
BYU -19
O/U 46.5
William Hill (New Jersey)
Advanced Stats
PPA + Success Rate agree → Sam Houston
· 73.9% ATS historically
↓ See full breakdown
Sam Houston 2023 Schedule
Sam Houston's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Sam Houston at BYU | +19.0L0–14 | 46.5 | L0–14 | U | Y |
| Sat 9/9 | Sam Houston vs Air Force | +13.5L3–13 | 36.5 | L3–13 | U | Y |
| — Bye Week — | ||||||
| Sat 9/23 | Sam Houston at Houston | +11.5L7–38 | 37.0 | L7–38 | O | N |
| Thu 9/28 | Sam Houston vs Jacksonville State | +6.5L28–35 | 36.5 | L28–35 | O | N |
| Thu 10/5 | Sam Houston at Liberty | +21.0L16–21 | 46.5 | L16–21 | U | Y |
| Wed 10/11 | Sam Houston at New Mexico State | +4.5L13–27 | 43.0 | L13–27 | U | N |
| Wed 10/18 | Sam Houston vs Florida International | -6.0L27–33 | 42.0 | L27–33 | O | N |
| Wed 10/25 | Sam Houston vs UTEP | -4.0L34–37 | 38.5 | L34–37 | O | N |
| Sat 11/4 | Sam Houston vs Kennesaw State | -16.5W24–21 | 41.5 | W24–21 | O | N |
| Sat 11/11 | Sam Houston at Louisiana Tech | +8.5W42–27 | 49.5 | W42–27 | O | Y |
| Sat 11/18 | Sam Houston at Western Kentucky | +12.5L23–28 | 52.0 | L23–28 | U | Y |
| Sat 11/25 | Sam Houston vs Middle Tennessee | +3.5W23–20 | 49.5 | W23–20 | U | Y |
BYU 2023 Schedule
BYU's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | BYU vs Sam Houston | -19.0W14–0 | 46.5 | W14–0 | U | N |
| Sat 9/9 | BYU vs Southern Utah | -30.5W41–16 | 46.5 | W41–16 | O | N |
| Sat 9/16 | BYU at Arkansas | +9.0W38–31 | 48.0 | W38–31 | O | Y |
| Sat 9/23 | BYU at Kansas | +9.0L27–38 | 55.5 | L27–38 | O | N |
| Fri 9/29 | BYU vs Cincinnati | -1.0W35–27 | 47.5 | W35–27 | O | Y |
| — Bye Week — | ||||||
| Sat 10/14 | BYU at TCU | +5.0L11–44 | 52.5 | L11–44 | O | N |
| Sat 10/21 | BYU vs Texas Tech | +3.0W27–14 | 49.0 | W27–14 | U | Y |
| Sat 10/28 | BYU at Texas | +20.5L6–35 | 48.5 | L6–35 | U | N |
| Sat 11/4 | BYU at West Virginia | +13.0L7–37 | 48.5 | L7–37 | U | N |
| Sat 11/11 | BYU vs Iowa State | +7.5L13–45 | 40.5 | L13–45 | O | N |
| Sat 11/18 | BYU vs Oklahoma | +24.5L24–31 | 58.5 | L24–31 | U | Y |
| Sat 11/25 | BYU at Oklahoma State | +15.5L34–40 | 55.5 | L34–40 | O | Y |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2023 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
→ Sam Houston
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 · 2023 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?
Sam Houston Edge
Sam Houston +0.00
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 0 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Sam Houston Edge
Sam Houston +0.0
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 0 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on BYU, 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
Sam Houston
K. C. Keeler #1
85–29 (75%)
· Yr 10 at school
OC
Brad Cornelsen
Yr 1
#1
DC
Clayton Carlin
Yr 1
#1
BYU
Kalani Sitake #1
59–34 (63%)
· Yr 8 at school
OC
Aaron Roderick
Yr 3
#1
DC
Jay Hill
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 ✓