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Toronto at Chicago: Steals

📊 $0 traded 🏦 Source: Kalshi
Total Volume
$0
Open Interest
0
Active Markets
12
Markets
12

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

All Outcomes (12)
Outcome Probability Yes Bid Yes Ask 24h Change Volume
Scottie Barnes: 1+ 0%
$0 Trade →
Scottie Barnes: 2+ 0%
$0 Trade →
Immanuel Quickley: 2+ 0%
$0 Trade →
RJ Barrett: 3+ 0%
$0 Trade →
Matas Buzelis: 1+ 0%
$0 Trade →
Matas Buzelis: 3+ 0%
$0 Trade →
Immanuel Quickley: 1+ 0%
$0 Trade →
Immanuel Quickley: 3+ 0%
$0 Trade →
RJ Barrett: 1+ 0%
$0 Trade →
Matas Buzelis: 2+ 0%
$0 Trade →
RJ Barrett: 2+ 0%
$0 Trade →
Scottie Barnes: 3+ 0%
$0 Trade →

About This Market

This market lets traders express views on how many steals will be recorded in the Toronto at Chicago game. It matters because steals reflect defensive pressure and tempo, and markets aggregate real‑time information about those factors.

The market focuses on a single matchup between Toronto and Chicago and offers 12 distinct outcomes that map to ranges or specific totals for steals. Historical team defensive profiles, pace of play, and current roster status shape expectations; because the market close time is listed as TBD, traders should monitor official lineup and injury updates leading into the game.

Market prices encode the crowd’s consensus about which steal ranges are most likely given current information; prices move as new data (lineups, injuries, rest, referee assignments) arrives. Treat odds as a dynamic summary of available information, not a fixed prediction.

Key Factors

Frequently Asked Questions

How will this market be settled and when should I expect settlement after the game?

Settlement is typically determined by the official league box score for the game; markets usually wait for any official stat corrections and settle after the final, confirmed box score is published. Check the market page for the exact settlement rule once the close time is set.

Which specific players or roles most directly influence the total steals outcome in Toronto at Chicago?

Primary ball‑handlers (point guards) influence turnover and steal opportunities, while leading perimeter defenders and wings who log high minutes drive steal counts. Bench defenders who receive significant minutes due to rotations or injuries can also swing totals.

How do late scratches or lineup changes affect this steals market?

Late scratches can materially change expected steals by shifting minutes, altering matchups, and changing team defensive assignments; markets typically react quickly when lineup news is reported.

What pregame signs should traders watch that tend to move prices for this market?

Monitor official starting lineups, injury reports, coach comments about rotations, back‑to‑back status, and any minutes restrictions. Also watch for unexpected rest decisions and reported illnesses or travel issues.

Does past head‑to‑head steals data between Toronto and Chicago reliably predict this market’s outcome?

Head‑to‑head history provides context but has limited predictive power by itself because steals depend heavily on current rosters, pace, and game context; use historical trends alongside up‑to‑date injury and lineup information.

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