| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Over 62.5 1H points scored | 48% | 42¢ | 48¢ | — | $60 | Trade → |
| Over 53.5 1H points scored | 71% | 71¢ | 90¢ | — | $1 | Trade → |
| Over 68.5 1H points scored | 0% | 13¢ | 32¢ | — | $0 | Trade → |
| Over 71.5 1H points scored | 0% | 2¢ | 23¢ | — | $0 | Trade → |
| Over 59.5 1H points scored | 0% | 47¢ | 69¢ | — | $0 | Trade → |
| Over 50.5 1H points scored | 0% | 47¢ | 100¢ | — | $0 | Trade → |
| Over 74.5 1H points scored | 0% | 0¢ | 100¢ | — | $0 | Trade → |
| Over 56.5 1H points scored | 0% | 60¢ | 81¢ | — | $0 | Trade → |
| Over 65.5 1H points scored | 0% | 20¢ | 40¢ | — | $0 | Trade → |
This market lets traders express expectations for the combined points scored in the first half of the Towson vs Hofstra game; it matters because first-half totals capture early-game pace and initial strategies that can differ from full-game outcomes.
Towson and Hofstra meet as collegiate basketball programs whose rosters, coaching staffs, and styles evolve each season; first-half scoring reflects opening lineups, tempo choices, and immediate matchup advantages rather than adjustments made later. This specific KALSHI listing is offered as nine discrete outcome ranges and currently shows $61 in total volume traded, with the market close time listed as TBD.
Market prices aggregate trader views about which first-half scoring range is most likely; use prices as a real-time signal of consensus expectations while remembering they are not guarantees.
The outcome is based on the official combined points scored by both teams during the regulation first half (the opening half of the game) as recorded in the official box score used by the settling authority; consult the platform’s rules for tie-breakers or voiding conditions.
Close and settlement timing are set by the platform; this listing currently shows the market close as TBD, so check the event page for updates — settlement will occur after the first half is completed and official stats are available.
Monitor availability of each team’s primary ball-handlers and top scorers, any announced starting lineup changes, and late injury or suspension reports—those personnel details most directly affect scoring and pace in the first half.
Past head-to-head first-half numbers can provide context, but sample sizes are often small and rosters/coaches change; use historical data alongside current-season form, matchup specifics, and injury news.
The nine outcomes partition possible first-half combined scores into discrete ranges or buckets; each outcome reflects trader consensus about that range being the correct one, so the distribution across outcomes gives a view of market-implied likely first-half scoring scenarios.