| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Over 211.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 214.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 217.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 220.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 223.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 226.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 229.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 232.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 235.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 238.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Over 241.5 points scored | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks how many total points will be scored in the Houston at Memphis game by offering discrete outcome buckets. It matters because it lets traders take positions on scoring expectations independent of which team wins.
Total-points markets are driven by both teams' offensive and defensive tendencies, current rosters, and game context (rest, travel, and matchup specifics). Changes such as injuries, recent form, or coaching strategy shifts can materially change expected scoring from one game to the next, so look at up-to-date team news alongside historical trends.
Odds on each outcome express how the market collectively prices the chance that the final combined score will fall into that outcome's range; treat odds as a consensus signal that incorporates public information and trader views.
The event page currently lists the market close as TBD; KALSHI typically closes such markets before the scheduled game start or at a platform-specified cutoff. Settlement is based on the official final combined score as reported by the relevant league.
The 11 outcomes split the range of possible combined scores into distinct buckets or exact totals the market will settle against. Each outcome covers a specific total-points interval or value; check the event page for the precise bucket definitions.
Monitor availability of each team's primary scorers, starting point guard(s) who control pace, and key interior defenders or rebounders. Late scratches or rotation changes to those roles tend to have the largest impact on game scoring.
Head-to-head history can reveal matchup tendencies, but it's a small sample and can be skewed by roster or coaching changes. Use recent meetings as context but prioritize current-season performance, lineup stability, and injury status.
Pre-game injury reports, announced starters, and late travel or rest news typically move market prices ahead of tip-off. After the game starts, only the final official score matters for settlement, so in-play events only influence pre-game pricing if they occur before the market closes.