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
Nebraska -27.5
O/U 49.0
DraftKings
Advanced Stats
PPA + Success Rate agree → Nebraska
· 73.9% ATS historically
↓ See full breakdown
UTEP 2024 Schedule
UTEP's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/31 | UTEP at Nebraska | +27.5L7–40 | 49.0 | L7–40 | U | N |
| Sat 9/7 | UTEP vs Southern Utah | -6.5L24–27 | 54.5 | L24–27 | U | N |
| Sat 9/14 | UTEP at Liberty | +23.5L10–28 | 57.5 | L10–28 | U | Y |
| Sat 9/21 | UTEP at Colorado State | +8.5L17–27 | 49.0 | L17–27 | U | N |
| — Bye Week — | ||||||
| Thu 10/3 | UTEP vs Sam Houston | +10.0L21–41 | 49.5 | L21–41 | O | N |
| Thu 10/10 | UTEP at Western Kentucky | +19.0L17–44 | 55.5 | L17–44 | O | N |
| Wed 10/16 | UTEP vs Florida International | +7.0W30–21 | 47.0 | W30–21 | O | Y |
| Tue 10/22 | UTEP at Louisiana Tech | +6.5L10–14 | 49.0 | L10–14 | U | Y |
| Sat 11/2 | UTEP vs Middle Tennessee | -2.0L13–20 | 48.0 | L13–20 | U | N |
| Sat 11/9 | UTEP vs Kennesaw State | -4.5W43–35 | 42.0 | W43–35 | O | Y |
| — Bye Week — | ||||||
| Sat 11/23 | UTEP at Tennessee | +41.5L0–56 | 54.0 | L0–56 | O | N |
| Sat 11/30 | UTEP at New Mexico State | +3.5W42–35 | 51.5 | W42–35 | O | Y |
Nebraska 2024 Schedule
Nebraska's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/31 | Nebraska vs UTEP | -27.5W40–7 | 49.0 | W40–7 | U | Y |
| Sat 9/7 | Nebraska vs Colorado | -6.5W28–10 | 55.0 | W28–10 | U | Y |
| Sat 9/14 | Nebraska vs Northern Iowa | -30.5W34–3 | 49.5 | W34–3 | U | Y |
| Fri 9/20 | Nebraska vs Illinois | -9.5L24–31 | 41.5 | L24–31 | O | N |
| Sat 9/28 | Nebraska at Purdue | -10.0W28–10 | 47.5 | W28–10 | U | Y |
| Sat 10/5 | Nebraska vs Rutgers | -7.0W14–7 | 39.5 | W14–7 | U | N |
| — Bye Week — | ||||||
| Sat 10/19 | Nebraska at Indiana | +6.5L7–56 | 48.0 | L7–56 | O | N |
| Sat 10/26 | Nebraska at Ohio State | +25.0L17–21 | 48.5 | L17–21 | U | Y |
| Sat 11/2 | Nebraska vs UCLA | -7.5L20–27 | 38.5 | L20–27 | O | N |
| — Bye Week — | ||||||
| Sat 11/16 | Nebraska at USC | +6.5L20–28 | 51.0 | L20–28 | U | N |
| Sat 11/23 | Nebraska vs Wisconsin | -1.5W44–25 | 40.5 | W44–25 | O | Y |
| Fri 11/29 | Nebraska at Iowa | +3.5L10–13 | 41.5 | L10–13 | U | Y |
| Sat 12/28 | Nebraska vs Boston College | -3.0W20–15 | 47.5 | W20–15 | U | Y |
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
Split
Metrics disagree
Elite · 82.4% ATS
PPA + PPO + Havoc
Split
Metrics disagree
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Nebraska
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?
UTEP Edge
UTEP +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?
UTEP Edge
UTEP +0.0
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 0 games this season
Actual Result
CSS Battle
Nebraska
4 — 0 sequences
✗ Predicted incorrectly
GC Battle
Nebraska
80.3 — 6.6 GC score
✗ Predicted incorrectly
Game Result
Nebraska won by 33
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Nebraska, 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
UTEP
Scotty Walden #1
0–0 (0%)
· Yr 1 at school
OC
Jake Brown
Yr 1
#1
DC
J. J. Clark
Yr 1
#1
Nebraska
Matt Rhule #1
5–7 (42%)
· Yr 2 at school
OC
Marcus Satterfield
Yr 2
#1
DC
Tony White
Yr 2
#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: CSS is not a predictive 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: GS is not a predictive 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: CSS is not a predictive 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: GS is not a predictive 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 ✓