Sat, Sep 11 2021
·
Week 2
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🏟 Jones AT&T Stadium
Lubbock, TX
·
Turf
·
60,862 cap
Stephen F. Austin✈ 441 miSame 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
Texas Tech -31.5
O/U 51.5
consensus
Stephen F. Austin 2021 Schedule
Stephen F. Austin's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| — Bye Week — | ||||||
| Sat 9/11 | Stephen F. Austin at Texas Tech | +31.5L22–28 | 51.5 | L22–28 | U | Y |
Texas Tech 2021 Schedule
Texas Tech's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/4 | Texas Tech vs Houston | +2.5W38–21 | 63.0 | W38–21 | U | Y |
| Sat 9/11 | Texas Tech vs Stephen F. Austin | -31.5W28–22 | 51.5 | W28–22 | U | N |
| Sat 9/18 | Texas Tech vs Florida International | -20.5W54–21 | 54.0 | W54–21 | O | Y |
| Sat 9/25 | Texas Tech at Texas | +9.0L35–70 | 63.0 | L35–70 | O | N |
| Sat 10/2 | Texas Tech at West Virginia | +7.5W23–20 | 55.0 | W23–20 | U | Y |
| Sat 10/9 | Texas Tech vs TCU | +2.5L31–52 | 60.0 | L31–52 | O | N |
| Sat 10/16 | Texas Tech at Kansas | -18.5W41–14 | 67.5 | W41–14 | U | Y |
| Sat 10/23 | Texas Tech vs Kansas State | +1.0L24–25 | 60.5 | L24–25 | U | Y |
| Sat 10/30 | Texas Tech at Oklahoma | +18.5L21–52 | 67.0 | L21–52 | O | N |
| — Bye Week — | ||||||
| Sat 11/13 | Texas Tech vs Iowa State | +13.0W41–38 | 55.5 | W41–38 | O | Y |
| Sat 11/20 | Texas Tech vs Oklahoma State | +10.0L0–23 | 55.0 | L0–23 | U | N |
| Sat 11/27 | Texas Tech at Baylor | +14.0L24–27 | 51.5 | L24–27 | U | Y |
| Tue 12/28 | Texas Tech vs Mississippi State | +10.0W34–7 | 58.5 | W34–7 | U | Y |
Momentum Control (CSS)
Consecutive Scoring Sequences
Who builds scoring momentum?
Stephen F. Austin Edge
Stephen F. Austin +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?
Stephen F. Austin Edge
Stephen F. Austin +0.0
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 1 game this season
Actual Result
CSS Battle
Tie
1 — 1 sequences
✗ Predicted incorrectly
GC Battle
Texas Tech
87.5 — 7.3 GC score
✗ Predicted incorrectly
Game Result
Texas Tech won by 6
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Texas Tech, 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.
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 ✓