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Miami (OH) at Ohio: Spread

📊 $3K traded 🏦 Source: Kalshi
Total Volume
$3K
Open Interest
3,167
Active Markets
11
Markets
11

Trade This Market

Yes Bid
Yes Ask
Last Price
Prev Close
Buy YES → Buy NO

Prices in cents (1¢ = 1%). Trade on Kalshi.

All Outcomes (11)
Outcome Probability Yes Bid Yes Ask 24h Change Volume
Miami (OH) wins by over 5.5 Points 51%
50¢ 51¢ $3K Trade →
Miami (OH) wins by over 11.5 Points 24%
25¢ 31¢ $164 Trade →
Miami (OH) wins by over 2.5 Points 65%
60¢ 65¢ $139 Trade →
Ohio wins by over 16.5 Points 1%
$63 Trade →
Ohio wins by over 19.5 Points 1%
$63 Trade →
Miami (OH) wins by over 8.5 Points 36%
36¢ 42¢ $20 Trade →
Ohio wins by over 7.5 Points 9%
16¢ $4 Trade →
Ohio wins by over 13.5 Points 3%
10¢ $3 Trade →
Ohio wins by over 1.5 Points 24%
25¢ 31¢ $2 Trade →
Ohio wins by over 4.5 Points 14%
15¢ 22¢ $1 Trade →
Ohio wins by over 10.5 Points 0%
12¢ $0 Trade →

About This Market

This prediction market asks which side of the point spread will cover in the college matchup between Miami (OH) and Ohio. It matters because spread markets aggregate information about injuries, weather, line movement, and bettor sentiment into a single, tradable measure of expectations.

Miami (OH) and Ohio are long-time Mid-American Conference rivals; games between them are often competitive and can hinge on small swings in field position, turnovers, and special teams. Historical home/away splits, recent form, and coaching matchups provide useful context but can shift quickly as rosters and injuries change during the season.

Odds and prices in a spread market represent the crowd’s collective view of which margin outcome is most likely given current information. Traders update prices as new facts arrive (injury reports, weather, in-game events), so prices reflect both fundamentals and changing sentiment rather than fixed truth.

Key Factors

Frequently Asked Questions

When will the Miami (OH) at Ohio: Spread market close?

The market close time is set by the platform (currently listed as TBD). Many spread markets close at official kickoff, but check the market page for the platform’s posted close time and any updates close to game day.

How do the multiple spread outcomes in this market map to what happens on the field?

Each spread outcome corresponds to a range of game margins — whether Miami (OH) covers, Ohio covers, or the game falls within a specific point range. Settlement depends on the final official score and the market’s defined cutoffs for each outcome.

Which historical trends between Miami (OH) and Ohio should I examine when evaluating this spread?

Look at recent head-to-head results, home versus away performance for each team, margin-of-victory patterns, and how each team has performed against similar offensive or defensive schemes this season rather than relying on distant historical data.

Which players or injury reports are most likely to move the Miami (OH) at Ohio spread?

Key starters — especially the projected starting quarterback, primary running back or leading receiver, and front-seven defensive leaders — tend to have the biggest impact. Late changes to kickers or starting linemen and official injury reports released 24–48 hours before kickoff are particularly market-moving.

How should live-game events (turnovers, injuries, momentum swings) be used to update positions in this spread market?

Monitor real-time stats, official injury updates, and play-by-play context: an early turnover or injury to a starter can justify quick re-evaluation, while isolated big plays matter less unless they change expected scoring trends. Use in-game information to reassess the expected margin and position size relative to remaining time and possession opportunities.

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