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
LSU -2
O/U 64.0
teamrankings
Advanced Stats
PPA + Success Rate agree → UCLA
· 73.9% ATS historically
↓ See full breakdown
LSU 2021 Schedule
LSU's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/4 | LSU at UCLA | -2.0L27–38 | 64.0 | L27–38 | O | N |
| Sat 9/11 | LSU vs McNeese | -39.0W34–7 | 66.0 | W34–7 | U | N |
| Sat 9/18 | LSU vs Central Michigan | -19.5W49–21 | 61.0 | W49–21 | O | Y |
| Sat 9/25 | LSU at Mississippi State | -1.5W28–25 | 54.5 | W28–25 | U | Y |
| Sat 10/2 | LSU vs Auburn | -2.5L19–24 | 57.0 | L19–24 | U | N |
| Sat 10/9 | LSU at Kentucky | +2.0L21–42 | 50.5 | L21–42 | O | N |
| Sat 10/16 | LSU vs Florida | +12.5W49–42 | 61.0 | W49–42 | O | Y |
| Sat 10/23 | LSU at Ole Miss | +9.0L17–31 | 76.5 | L17–31 | U | N |
| — Bye Week — | ||||||
| Sat 11/6 | LSU at Alabama | +29.5L14–20 | 66.5 | L14–20 | U | Y |
| Sat 11/13 | LSU vs Arkansas | +3.0L13–16 | 59.5 | L13–16 | U | Y |
| Sat 11/20 | LSU vs UL Monroe | -29.0W27–14 | 57.5 | W27–14 | U | N |
| Sat 11/27 | LSU vs Texas A&M | +6.0W27–24 | 47.0 | W27–24 | O | Y |
| Tue 1/4 | LSU vs Kansas State | +9.5L20–42 | 47.0 | L20–42 | O | N |
UCLA 2021 Schedule
UCLA's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/28 | UCLA vs Hawai'i | -17.5W44–10 | 67.0 | W44–10 | U | Y |
| Sat 9/4 | UCLA vs LSU | +2.0W38–27 | 64.0 | W38–27 | O | Y |
| — Bye Week — | ||||||
| Sat 9/18 | UCLA vs Fresno State | -11.0L37–40 | 64.0 | L37–40 | O | N |
| Sat 9/25 | UCLA at Stanford | -4.0W35–24 | 60.5 | W35–24 | U | Y |
| Sat 10/2 | UCLA vs Arizona State | -3.0L23–42 | 56.5 | L23–42 | O | N |
| Sat 10/9 | UCLA at Arizona | -16.0W34–16 | 60.0 | W34–16 | U | Y |
| Sat 10/16 | UCLA at Washington | +1.5W24–17 | 55.5 | W24–17 | U | Y |
| Sat 10/23 | UCLA vs Oregon | -1.0L31–34 | 62.5 | L31–34 | O | N |
| Sat 10/30 | UCLA at Utah | +6.0L24–44 | 60.5 | L24–44 | O | N |
| — Bye Week — | ||||||
| Sat 11/13 | UCLA vs Colorado | -18.0W44–20 | 57.5 | W44–20 | O | Y |
| Sat 11/20 | UCLA at USC | -4.5W62–33 | 66.5 | W62–33 | O | Y |
| Sat 11/27 | UCLA vs California | -6.5W42–14 | 58.5 | W42–14 | U | Y |
| Tue 12/28 | UCLA vs NC State | +2.0 | 60.0 | — | — | — |
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
Split
Metrics disagree
Elite · 82.4% ATS
PPA + PPO + Havoc
Split
Metrics disagree
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ UCLA
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?
LSU Edge
LSU +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?
LSU Edge
LSU +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
UCLA
2 — 0 sequences
✗ Predicted incorrectly
GC Battle
UCLA
53.2 — 15.3 GC score
✗ Predicted incorrectly
Game Result
UCLA won by 11
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on UCLA, 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
LSU
Ed Orgeron #1
47–15 (76%)
· Yr 6 at school
OC
Jake Peetz
Yr 1
#1
DC
Daronte Jones
Yr 1
#1
UCLA
Chip Kelly #1
12–22 (35%)
· Yr 4 at school
OC
Justin Frye
Yr 1
#1
DC
Jerry Azzinaro
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: Momentum Control is a great measure for predicting game outcome but NOT an 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: Game Control is another great measure for predicting game outcome but NOT an 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: Momentum Control is a great measure for predicting game outcome but NOT an 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: Game Control is another great measure for predicting game outcome but NOT an 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 ✓