Overview
CS FullertonRecent Form
CS Fullerton's last 5 matches: 0 wins, 0 draws, 5 losses. Most recent game was against UC Riverside. Recent form is one of the strongest predictors of upcoming match outcomes.
Match detail UC San Diego vs CS Fullerton — line-ups, stats, oddsL
UC San DiegoAway
100 – 552 Mar 2025
Form in numbers
Current run10× loss
58.8
Avg scored
84.4
Avg conceded
0%
Win rate
Over the last 10 matches
Season Statistics
(2024-2025)Scoring Overview
63.25
Pts For
77.34
Pts Against
13.3
Avg Win Margin
140.6
Total Pts
12.5%
Close games (≤5 pts)
40.6%
Blowouts (20+ pts)
0.0%
Comeback Rate
Match Outcomes
Win / loss distribution by margin
1–5 pts
1
3
6–10 pts
2
6
11–20 pts
2
6
21+ pts
1
11
Statistics
Sport
The sport context for this club season. Use it to jump back to the sport overview with leagues, clubs and results.Matches Played
Total matches included in this season record. It defines the sample size behind the win, loss and scoring metrics.32
Blowouts
Games decided by a large margin. Blowouts show how often a team separates from opponents or gets exposed, useful for handicap and alternate run-line markets.13
Overtime Games
Number of games that required overtime. Useful for judging close-game frequency and fatigue.0
Blowout Pct
Percentage of games decided by a large margin. A higher rate supports checking run lines and alternate handicaps instead of only standard moneyline prices.40.6%
Close Games
Number of games decided by a narrow margin. A high count points to volatile late-game spots where run-line, moneyline and bullpen matchups deserve extra attention.4
Avg Total Points
Average combined points in the team's games. Useful for judging tempo and totals markets.140.60
Comeback Rate
Share of games with a comeback pattern. It helps judge whether live underdog prices after an early deficit may still carry value.0.0%
Comeback Wins
Wins after trailing earlier in the game. This highlights resilience and late scoring, useful for live betting when the team falls behind at a playable price.0
Close Game Pct
Percentage of games decided by a narrow margin. High values suggest tighter pricing, late variance and a need to compare moneyline against handicap markets.12.5%
Avg Losing Margin
Average margin in the team's losses. Smaller margins may indicate competitiveness despite losses, while larger margins warn against aggressive handicap backing.20.40
Avg Winning Margin
Average margin in the team's wins. Bigger margins can support run-line confidence, while small margins suggest moneyline may be safer than handicap markets.13.30
API data: 10 May 2026 · Stats updated: 10 Jul 2026