Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Texas A&M,
while Game Control favors Tennessee.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
73.7%
Texas A&M wins
Solid
Game Control
50.6%
Tennessee wins
Toss-up
Vegas Spread
Tennessee -3
O/U 54.5
DraftKings
Advanced Stats
3 factors agree (PPA + PPO + Havoc) → Texas A&M
· 82.4% ATS historically
↓ See full breakdown
Texas A&M 2023 Schedule
Texas A&M's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Texas A&M vs New Mexico | -37.5W52–10 | 48.5 | W52–10 | O | Y |
| Sat 9/9 | Texas A&M at Miami | -3.0L33–48 | 50.5 | L33–48 | O | N |
| Sat 9/16 | Texas A&M vs UL Monroe | -36.5W47–3 | 53.5 | W47–3 | U | Y |
| Sat 9/23 | Texas A&M vs Auburn | -9.5W27–10 | 51.0 | W27–10 | U | Y |
| Sat 9/30 | Texas A&M vs Arkansas | -6.5W34–22 | 53.5 | W34–22 | O | Y |
| Sat 10/7 | Texas A&M vs Alabama | +2.5L20–26 | 45.0 | L20–26 | O | N |
| Sat 10/14 | Texas A&M at Tennessee | +3.0L13–20 | 54.5 | L13–20 | U | N |
| — Bye Week — | ||||||
| Sat 10/28 | Texas A&M vs South Carolina | -17.0W30–17 | 51.5 | W30–17 | U | N |
| Sat 11/4 | Texas A&M at Ole Miss | +3.0L35–38 | 52.5 | L35–38 | O | Y |
| Sat 11/11 | Texas A&M vs Mississippi State | -16.5W51–10 | 40.5 | W51–10 | O | Y |
| Sat 11/18 | Texas A&M vs Abilene Christian | -40.5W38–10 | 54.5 | W38–10 | U | N |
| Sat 11/25 | Texas A&M at LSU | +10.5L30–42 | 67.5 | L30–42 | O | N |
| Wed 12/27 | Texas A&M vs Oklahoma State | +4.0L23–31 | 56.0 | L23–31 | U | N |
Tennessee 2023 Schedule
Tennessee's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Tennessee vs Virginia | -27.5W49–13 | 56.0 | W49–13 | O | Y |
| Sat 9/9 | Tennessee vs Austin Peay | -48.0W30–13 | 65.5 | W30–13 | U | N |
| Sat 9/16 | Tennessee at Florida | -5.0L16–29 | 57.0 | L16–29 | U | N |
| Sat 9/23 | Tennessee vs UTSA | -24.0W45–14 | 59.0 | W45–14 | U | Y |
| Sat 9/30 | Tennessee vs South Carolina | -12.0W41–20 | 59.0 | W41–20 | O | Y |
| — Bye Week — | ||||||
| Sat 10/14 | Tennessee vs Texas A&M | -3.0W20–13 | 54.5 | W20–13 | U | Y |
| Sat 10/21 | Tennessee at Alabama | +8.5L20–34 | 47.5 | L20–34 | O | N |
| Sat 10/28 | Tennessee at Kentucky | -4.0W33–27 | 50.5 | W33–27 | O | Y |
| Sat 11/4 | Tennessee vs UConn | -35.0W59–3 | 55.5 | W59–3 | O | Y |
| Sat 11/11 | Tennessee at Missouri | -1.0L7–36 | 58.5 | L7–36 | U | N |
| Sat 11/18 | Tennessee vs Georgia | +9.0L10–38 | 59.0 | L10–38 | U | N |
| Sat 11/25 | Tennessee vs Vanderbilt | -27.0W48–24 | 58.0 | W48–24 | O | N |
| Mon 1/1 | Tennessee vs Iowa | -4.5W35–0 | 37.0 | W35–0 | 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
Split
Metrics disagree
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Texas A&M
Elite · 73.9% ATS
PPA + Success Rate
Split
Metrics disagree
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?
Texas A&M Edge
Texas A&M +1.00
CSS Edge (season-to-date)
Teams with this edge win 73.7% of games historically
Based on 4 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Tennessee Edge
Tennessee +0.7
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 5 games 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
Texas A&M
Jimbo Fisher #1
0–0 (0%)
· Yr 1 at school
OC
Bobby Petrino
Yr 1
#1
DC
D. J. Durkin
Yr 2
#1
Tennessee
Josh Heupel #1
20–9 (69%)
· Yr 3 at school
OC
Joey Halzle
Yr 1
#1
DC
Tim Banks
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: 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 ✓