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
Houston -3.0
O/U 56.0
Bovada
Advanced Stats
All 4 factors agree → UNLV
· 83.1% ATS historically when all four align
↓ See full breakdown
UNLV 2024 Schedule
UNLV's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/31 | UNLV at Houston | +3.0W27–7 | 56.0 | W27–7 | U | Y |
| Sat 9/7 | UNLV vs Utah Tech | -41.5W72–14 | 55.5 | W72–14 | O | Y |
| Fri 9/13 | UNLV vs Kansas | +7.0W23–20 | 57.0 | W23–20 | U | Y |
| — Bye Week — | ||||||
| Sat 9/28 | UNLV vs Fresno State | -2.5W59–14 | 51.0 | W59–14 | O | Y |
| Fri 10/4 | UNLV vs Syracuse | -5.5L41–44 | 55.5 | L41–44 | O | N |
| Fri 10/11 | UNLV at Utah State | -19.0W50–34 | 67.5 | W50–34 | O | N |
| Sat 10/19 | UNLV at Oregon State | -6.5W33–25 | 61.0 | W33–25 | U | Y |
| Fri 10/25 | UNLV vs Boise State | +4.0L24–29 | 64.0 | L24–29 | U | N |
| — Bye Week — | ||||||
| Sat 11/9 | UNLV at Hawai'i | -12.0W29–27 | 51.5 | W29–27 | O | N |
| Sat 11/16 | UNLV vs San Diego State | -22.0W41–20 | 55.5 | W41–20 | O | N |
| Fri 11/22 | UNLV at San José State | -7.5W27–16 | 59.5 | W27–16 | U | Y |
| Sat 11/30 | UNLV vs Nevada | -17.5W38–14 | 54.5 | W38–14 | U | Y |
| Fri 12/6 | UNLV at Boise State | +3.5L7–21 | 57.5 | L7–21 | U | N |
| Wed 12/18 | UNLV vs California | -3.0W24–13 | 45.0 | W24–13 | U | Y |
Houston 2024 Schedule
Houston's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/31 | Houston vs UNLV | -3.0L7–27 | 56.0 | L7–27 | U | N |
| Sat 9/7 | Houston at Oklahoma | +27.5L12–16 | 48.5 | L12–16 | U | Y |
| Sat 9/14 | Houston vs Rice | -3.5W33–7 | 43.5 | W33–7 | U | Y |
| Sat 9/21 | Houston at Cincinnati | +4.0L0–34 | 47.5 | L0–34 | U | N |
| Sat 9/28 | Houston vs Iowa State | +16.0L0–20 | 43.0 | L0–20 | U | N |
| Fri 10/4 | Houston at TCU | +16.5W30–19 | 52.0 | W30–19 | U | Y |
| — Bye Week — | ||||||
| Sat 10/19 | Houston vs Kansas | +4.5L14–42 | 45.5 | L14–42 | O | N |
| Sat 10/26 | Houston vs Utah | +4.5W17–14 | 36.0 | W17–14 | U | Y |
| Sat 11/2 | Houston vs Kansas State | +12.5W24–19 | 46.5 | W24–19 | U | Y |
| — Bye Week — | ||||||
| Fri 11/15 | Houston at Arizona | +1.0L3–27 | 46.5 | L3–27 | U | N |
| Sat 11/23 | Houston vs Baylor | +7.0L10–20 | 51.0 | L10–20 | U | N |
| Sat 11/30 | Houston at BYU | +9.5L18–30 | 39.5 | L18–30 | O | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2024 season
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
All 4 Agree
→ UNLV
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ UNLV
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ UNLV
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 · 2024 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?
UNLV Edge
UNLV +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?
UNLV Edge
UNLV +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 Houston, 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
UNLV
Barry Odom #1
9–5 (64%)
· Yr 2 at school
OC
Brennan Marion
Yr 2
#1
DC
Michael Scherer
Yr 2
#1
Houston
Willie Fritz #1
0–0 (0%)
· Yr 1 at school
OC
Kevin Barbay
Yr 1
#1
DC
Shiel Wood
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 ✓