| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Over 133.5 points scored | 45% | 45¢ | 46¢ | — | $2K | Trade → |
| Over 145.5 points scored | 0% | 18¢ | 25¢ | — | $0 | Trade → |
| Over 136.5 points scored | 0% | 39¢ | 44¢ | — | $0 | Trade → |
| Over 124.5 points scored | 0% | 68¢ | 73¢ | — | $0 | Trade → |
| Over 121.5 points scored | 0% | 73¢ | 80¢ | — | $0 | Trade → |
| Over 148.5 points scored | 0% | 13¢ | 20¢ | — | $0 | Trade → |
| Over 130.5 points scored | 0% | 54¢ | 59¢ | — | $0 | Trade → |
| Over 127.5 points scored | 0% | 61¢ | 66¢ | — | $0 | Trade → |
| Over 139.5 points scored | 0% | 32¢ | 37¢ | — | $0 | Trade → |
| Over 142.5 points scored | 0% | 25¢ | 30¢ | — | $0 | Trade → |
| Over 118.5 points scored | 0% | 78¢ | 85¢ | — | $0 | Trade → |
This market asks how many total points will be scored in the college basketball game between Fordham and La Salle. It matters because total-points markets synthesize market expectations about pace, shooting, and game context into a single, tradable proposition.
Fordham and La Salle are collegiate programs whose matchups can reflect differing styles of play, roster turnover, and coaching philosophies; those elements shape scoring outcomes. Seasonal form, recent injuries, and whether the game is home or away for La Salle all provide ongoing context that traders use when updating their views.
Market odds express the crowd’s aggregated expectation for the combined score and change as new information arrives (injuries, lineup news, rest). They are not guarantees but a real-time consensus that incorporates many observable factors.
It refers to the combined number of points scored by both teams in the game as defined by this market; check the market rules for whether overtime is included or excluded because resolution depends on that specification.
Market prices typically move quickly when information about key players or starters is released, because missing or returning scorers change expected possessions, usage distribution, and shooting efficiency, all of which influence the projected total.
Head-to-head results can highlight matchup tendencies (e.g., one team historically forcing a slower pace), but small sample sizes and roster turnover in college basketball limit reliability; treat historical trends as one input among many.
Home-court advantage can improve a host’s shooting efficiency and comfort, and reduce travel fatigue, potentially increasing scoring; however, the net effect on the total depends on both teams’ styles and situational factors like rest and injuries.
The market’s close time will be set by the market operator (currently listed as to-be-determined); resolution normally uses the official final game score reported by the sport’s governing body and follows the market’s published rules, so monitor the market page for updates.