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
Illinois -4.5
O/U 52.0
teamrankings
Advanced Stats
All 4 factors agree → UTSA
· 83.1% ATS historically when all four align
↓ See full breakdown
UTSA 2021 Schedule
UTSA's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/4 | UTSA at Illinois | +4.5W37–30 | 52.0 | W37–30 | O | Y |
| Sat 9/11 | UTSA vs Lamar | -38.0W54–0 | 65.0 | W54–0 | U | Y |
| Sat 9/18 | UTSA vs Middle Tennessee | -11.5W27–13 | 60.0 | W27–13 | U | Y |
| Sat 9/25 | UTSA at Memphis | +3.0W31–28 | 66.5 | W31–28 | U | Y |
| Sat 10/2 | UTSA vs UNLV | -21.5W24–17 | 55.5 | W24–17 | U | N |
| Sat 10/9 | UTSA at Western Kentucky | +3.5W52–46 | 71.0 | W52–46 | O | Y |
| Sat 10/16 | UTSA vs Rice | -17.0W45–0 | 53.0 | W45–0 | U | Y |
| Sat 10/23 | UTSA at Louisiana Tech | -5.5W45–16 | 59.5 | W45–16 | O | Y |
| — Bye Week — | ||||||
| Sat 11/6 | UTSA at UTEP | -12.0W44–23 | 53.5 | W44–23 | O | Y |
| Sat 11/13 | UTSA vs Southern Miss | -32.5W27–17 | 54.0 | W27–17 | U | N |
| Sat 11/20 | UTSA vs UAB | -3.5W34–31 | 54.0 | W34–31 | O | N |
| Sat 11/27 | UTSA at North Texas | -8.5L23–45 | 60.0 | L23–45 | O | N |
| Fri 12/3 | UTSA vs Western Kentucky | +3.0W49–41 | 74.5 | W49–41 | O | Y |
| Tue 12/21 | UTSA vs San Diego State | +3.0L24–38 | 48.0 | L24–38 | O | N |
Illinois 2021 Schedule
Illinois's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/28 | Illinois vs Nebraska | +6.5W30–22 | 52.0 | W30–22 | U | Y |
| Sat 9/4 | Illinois vs UTSA | -4.5L30–37 | 52.0 | L30–37 | O | N |
| Sat 9/11 | Illinois at Virginia | +10.5L14–42 | 57.0 | L14–42 | U | N |
| Fri 9/17 | Illinois vs Maryland | +7.0L17–20 | 61.5 | L17–20 | U | Y |
| Sat 9/25 | Illinois at Purdue | +10.5L9–13 | 53.5 | L9–13 | U | Y |
| Sat 10/2 | Illinois vs Charlotte | -10.0W24–14 | 54.0 | W24–14 | U | N |
| Sat 10/9 | Illinois vs Wisconsin | +12.5L0–24 | 42.0 | L0–24 | U | N |
| — Bye Week — | ||||||
| Sat 10/23 | Illinois at Penn State | +24.5W20–18 | 46.0 | W20–18 | U | Y |
| Sat 10/30 | Illinois vs Rutgers | +1.5L14–20 | 41.5 | L14–20 | U | N |
| Sat 11/6 | Illinois at Minnesota | +14.5W14–6 | 44.5 | W14–6 | U | Y |
| — Bye Week — | ||||||
| Sat 11/20 | Illinois at Iowa | +12.0L23–33 | 37.5 | L23–33 | O | Y |
| Sat 11/27 | Illinois vs Northwestern | -7.0W47–14 | 45.0 | W47–14 | O | Y |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2021 season
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
All 4 Agree
→ UTSA
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ UTSA
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ UTSA
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 · 2021 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?
UTSA Edge
UTSA +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?
UTSA Edge
UTSA +0.0
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 1 game this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Illinois, 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
UTSA
Jeff Traylor #1
10–5 (67%)
· Yr 2 at school
OC
Barry Lunney Jr.
Yr 1
#1
DC
Jess Loepp / Rod Wright
Yr 1
#1
Illinois
Bret Bielema #1
1–3 (25%)
· Yr 1 at school
OC
Tony Petersen
Yr 1
#1
DC
Ryan Walters
Yr 1
#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 ✓