Sat, Sep 9 2023
·
Week 2
·
🏟 Jones AT&T Stadium
Lubbock, TX
·
Turf
·
60,862 cap
Oregon✈ 1,344 mi+2 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
75.9%
Oregon wins
Solid
Vegas Spread
Oregon -4.5
O/U 70.0
William Hill (New Jersey)
Advanced Stats
All 4 factors agree → Oregon
· 83.1% ATS historically when all four align
↓ See full breakdown
Oregon 2023 Schedule
Oregon's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Oregon vs Portland State | -48.0W81–7 | 64.5 | W81–7 | O | Y |
| Sat 9/9 | Oregon at Texas Tech | -4.5W38–30 | 70.0 | W38–30 | U | Y |
| Sat 9/16 | Oregon vs Hawai'i | -38.5W55–10 | 67.5 | W55–10 | U | Y |
| Sat 9/23 | Oregon vs Colorado | -21.0W42–6 | 70.0 | W42–6 | U | Y |
| Sat 9/30 | Oregon at Stanford | -27.0W42–6 | 59.5 | W42–6 | U | Y |
| — Bye Week — | ||||||
| Sat 10/14 | Oregon at Washington | +3.0L33–36 | 67.0 | L33–36 | O | Y |
| Sat 10/21 | Oregon vs Washington State | -19.5W38–24 | 60.5 | W38–24 | O | N |
| Sat 10/28 | Oregon at Utah | -6.5W35–6 | 47.5 | W35–6 | U | Y |
| Sat 11/4 | Oregon vs California | -26.5W63–19 | 61.5 | W63–19 | O | Y |
| Sat 11/11 | Oregon vs USC | -12.5W36–27 | 78.5 | W36–27 | U | N |
| Sat 11/18 | Oregon at Arizona State | -21.5W49–13 | 52.5 | W49–13 | O | Y |
| Fri 11/24 | Oregon vs Oregon State | -14.0W31–7 | 61.5 | W31–7 | U | Y |
| Fri 12/1 | Oregon vs Washington | -9.0L31–34 | 67.0 | L31–34 | U | N |
| Mon 1/1 | Oregon vs Liberty | -18.5W45–6 | 71.5 | W45–6 | U | Y |
Texas Tech 2023 Schedule
Texas Tech's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Texas Tech at Wyoming | -13.0L33–35 | 50.5 | L33–35 | O | N |
| Sat 9/9 | Texas Tech vs Oregon | +4.5L30–38 | 70.0 | L30–38 | U | N |
| Sat 9/16 | Texas Tech vs Tarleton State | -36.5W41–3 | 75.5 | W41–3 | U | Y |
| Sat 9/23 | Texas Tech at West Virginia | -6.0L13–20 | 53.5 | L13–20 | U | N |
| Sat 9/30 | Texas Tech vs Houston | -8.5W49–28 | 52.0 | W49–28 | O | Y |
| Sat 10/7 | Texas Tech at Baylor | -2.5W39–14 | 59.5 | W39–14 | U | Y |
| Sat 10/14 | Texas Tech vs Kansas State | -1.0L21–38 | 57.0 | L21–38 | O | N |
| Sat 10/21 | Texas Tech at BYU | -3.0L14–27 | 49.0 | L14–27 | U | N |
| — Bye Week — | ||||||
| Thu 11/2 | Texas Tech vs TCU | -2.5W35–28 | 59.5 | W35–28 | O | Y |
| Sat 11/11 | Texas Tech at Kansas | +3.5W16–13 | 61.5 | W16–13 | U | Y |
| Sat 11/18 | Texas Tech vs UCF | -2.0W24–23 | 59.0 | W24–23 | U | N |
| Fri 11/24 | Texas Tech at Texas | +16.5L7–57 | 53.5 | L7–57 | O | N |
| Sat 12/16 | Texas Tech vs California | -3.5W34–14 | 54.5 | W34–14 | U | 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
All 4 Agree
→ Oregon
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Oregon
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Oregon
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?
Oregon Edge
Oregon +0.00
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 1 game this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Oregon Edge
Oregon +23.7
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 1 game this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
CSS and GC disagree on this matchup. When the metrics split, historical cover rates are essentially random — treat this as a coin flip against the spread.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Oregon
Dan Lanning #1
13–3 (81%)
· Yr 2 at school
OC
Junior Adams
Yr 1
#1
DC
Tosh Lupoi
Yr 2
#1
Texas Tech
Joey McGuire #1
9–7 (56%)
· Yr 2 at school
OC
Zach Kittley
Yr 2
#1
DC
Tim DeRuyter
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 ✓