Matchup Prediction
UNLV
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
UNLV entering this game.
Momentum Control
73.7%
UNLV wins
Solid
Game Control
75.9%
UNLV wins
Solid
Vegas Spread
UTEP -1
O/U 49.5
William Hill (New Jersey)
Advanced Stats
PPA + Success Rate agree → UNLV
· 73.9% ATS historically
↓ See full breakdown
UNLV 2023 Schedule
UNLV's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | UNLV vs Bryant | -16.5W44–14 | 66.0 | W44–14 | U | Y |
| Sat 9/9 | UNLV at Michigan | +38.0L7–35 | 57.5 | L7–35 | U | Y |
| Sat 9/16 | UNLV vs Vanderbilt | +4.5W40–37 | 56.5 | W40–37 | O | Y |
| Sat 9/23 | UNLV at UTEP | +1.0W45–28 | 49.5 | W45–28 | O | Y |
| Sat 9/30 | UNLV vs Hawai'i | -10.5W44–20 | 58.5 | W44–20 | O | Y |
| — Bye Week — | ||||||
| Sat 10/14 | UNLV at Nevada | -7.5W45–27 | 51.5 | W45–27 | O | Y |
| Sat 10/21 | UNLV vs Colorado State | -6.5W25–23 | 60.0 | W25–23 | U | N |
| Sat 10/28 | UNLV at Fresno State | +10.5L24–31 | 56.0 | L24–31 | U | Y |
| Sat 11/4 | UNLV at New Mexico | -10.0W56–14 | 61.0 | W56–14 | O | Y |
| Fri 11/10 | UNLV vs Wyoming | -2.5W34–14 | 48.5 | W34–14 | U | Y |
| Sat 11/18 | UNLV at Air Force | +2.5W31–27 | 46.5 | W31–27 | O | Y |
| Sat 11/25 | UNLV vs San José State | -3.5L31–37 | 58.5 | L31–37 | O | N |
| Sat 12/2 | UNLV vs Boise State | +2.5L20–44 | 58.0 | L20–44 | O | N |
| Tue 12/26 | UNLV vs Kansas | +8.0L36–49 | 64.5 | L36–49 | O | N |
UTEP 2023 Schedule
UTEP's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/26 | UTEP at Jacksonville State | -1.5L14–17 | 54.5 | L14–17 | U | N |
| Sat 9/2 | UTEP vs Incarnate Word | -7.5W28–14 | 57.5 | W28–14 | U | Y |
| Sat 9/9 | UTEP at Northwestern | +1.0L7–38 | 40.0 | L7–38 | O | N |
| Sat 9/16 | UTEP at Arizona | +18.0L10–31 | 57.0 | L10–31 | U | N |
| Sat 9/23 | UTEP vs UNLV | -1.0L28–45 | 49.5 | L28–45 | O | N |
| Fri 9/29 | UTEP vs Louisiana Tech | +2.0L10–24 | 49.5 | L10–24 | U | N |
| — Bye Week — | ||||||
| Wed 10/11 | UTEP at Florida International | -1.5W27–14 | 44.0 | W27–14 | U | Y |
| Wed 10/18 | UTEP vs New Mexico State | +3.0L7–28 | 48.5 | L7–28 | U | N |
| Wed 10/25 | UTEP at Sam Houston | +4.0W37–34 | 38.5 | W37–34 | O | Y |
| Sat 11/4 | UTEP vs Western Kentucky | +9.5L13–21 | 54.5 | L13–21 | U | Y |
| — Bye Week — | ||||||
| Sat 11/18 | UTEP at Middle Tennessee | +8.5L30–34 | 48.5 | L30–34 | O | Y |
| Sat 11/25 | UTEP vs Liberty | +18.0L28–42 | 54.5 | L28–42 | 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
→ 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 · 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?
UNLV Edge
UNLV +1.00
CSS Edge (season-to-date)
Teams with this edge win 73.7% of games historically
Based on 3 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
UNLV Edge
UNLV +25.4
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 4 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on UNLV with a large edge. Historically, dominant teams like this are fully priced into the spread — the agreed-upon team covers just 50.2% of the time. The metrics predict game control better than they beat the number.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
UNLV
Barry Odom #1
2–1 (67%)
· Yr 1 at school
OC
Brennan Marion
Yr 1
#1
DC
Michael Scherer
Yr 1
#1
UTEP
Dana Dimel #1
18–43 (30%)
· Yr 6 at school
OC
Scotty Ohara
Yr 1
#1
DC
Bradley Dale Peveto
Yr 3
#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 ✓