| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Over 136.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 133.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 139.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 168.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 142.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 160.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 163.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 157.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 166.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 148.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 151.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 154.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 145.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks how many total points will be scored in the college basketball game Saint Joseph's at New Mexico, divided into discrete outcome ranges. It matters because aggregated trading reveals how participants expect pace, offense, and defense to interact in this specific matchup.
Saint Joseph's and New Mexico are NCAA programs with differing styles, travel considerations, and roster compositions that influence scoring. Venue factors (New Mexico's home environment), recent team form, and available personnel all shape scoring expectations. Historical head-to-head results may be limited, so season-to-date team statistics and recent games are the best context for assessing likely totals.
Market prices represent traders' collective expectations about the distribution of possible total-point outcomes and will move as new information (injuries, lineup changes, weather for travel, etc.) arrives. Use prices as a real-time signal of consensus while also checking the underlying game-level data yourself.
Trading typically closes at the market’s scheduled close time or at game start; this market currently shows the close as TBD, so check the KALSHI platform or the market page for an updated cutoff before placing trades.
The market is divided into 11 discrete total-point outcome buckets covering different scoring ranges; view the market on KALSHI to see the exact labeled ranges and which range corresponds to each outcome.
Home advantages such as familiar routines, crowd influence, and altitude in Albuquerque can impact player stamina and shooting; those factors can suppress or enhance scoring, particularly late in the game, and are therefore reflected in market pricing once traders factor them in.
Monitor injury reports, starting lineup announcements, recent scoring trends, turnover and rebound rates, and any coaching adjustments; changes to primary shooters or ball-handlers are especially material to total-point expectations.
Late news often moves prices rapidly as traders update expectations; the magnitude of the move depends on the importance of the player affected, available liquidity, and whether multiple market participants act on the same information.