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Portland at Minnesota: Steals

📊 $0 traded 🏦 Source: Kalshi
Total Volume
$0
Open Interest
0
Active Markets
9
Markets
9

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

All Outcomes (9)
Outcome Probability Yes Bid Yes Ask 24h Change Volume
Donte DiVincenzo: 3+ 0%
$0 Trade →
Jaden McDaniels: 1+ 0%
$0 Trade →
Donte DiVincenzo: 2+ 0%
$0 Trade →
Toumani Camara: 3+ 0%
$0 Trade →
Donte DiVincenzo: 1+ 0%
$0 Trade →
Jaden McDaniels: 2+ 0%
$0 Trade →
Toumani Camara: 1+ 0%
$0 Trade →
Jaden McDaniels: 3+ 0%
$0 Trade →
Toumani Camara: 2+ 0%
$0 Trade →

About This Market

This market is about how many steals will be recorded in the Portland at Minnesota game; steals are a discrete stat that can change possession and swing short-term momentum, making them a focused micro-bet for game bettors and traders.

Portland and Minnesota each bring distinct defensive profiles and rotation patterns that influence turnover creation: one team may rely on aggressive on-ball pressure while the other contests passing lanes with length. Season-to-date trends, recent opponent matchups, and any roster or coaching changes entering the matchup all provide context for expected steal rates.

Market prices reflect traders’ collective assessment of which steal totals are most likely given available information; price moves typically incorporate new public information like injury news, starting lineups, and tempo projections rather than a fixed prediction.

Key Factors

Frequently Asked Questions

What exactly do the nine outcomes represent for the Portland at Minnesota: Steals market?

Each outcome corresponds to a specific steal total or a range of steal totals as defined by the contract on the market page; outcomes are mutually exclusive and one outcome will be paid based on the official steals recorded in the game.

When does this market close and when will settlement occur?

The market close time is listed on the event page (currently TBD); settlement normally occurs after the official game box score is published by the league, and final outcomes can be delayed if the league issues statistical corrections or reviews.

How do last-minute lineup changes or in-game rotations affect which outcome is likely?

Late lineup or rotation updates can materially shift expected steals because different defenders and ball-handlers create different turnover profiles; market prices often move up to tip-off as this information becomes public.

Which players or roles on Portland and Minnesota most directly influence steals in this matchup?

Primary on-ball defenders, quick perimeter guards, active wings who gamble for deflections, and any bench defenders who earn significant minutes are the roles most likely to affect the game’s steal total.

How should I use historical team steal rates or team-vs-team history when evaluating this market?

Use recent steals-per-game and turnover tendencies as a baseline but adjust for current rotations, injuries, and pace differences; head-to-head history can help but is often a small sample and should be weighed alongside recent form and lineup continuity.

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