SimpleFunctions
KalshiMay 24, 202615 days left

Game 3: Oklahoma City at Los Angeles L Winner?

This contract is priced at 77¢ on Kalshi. Current book: 76¢ bid, 77¢ ask, 1¢ spread.

Implied probability

77¢
$206K volume
$194K liquidity
28% of event volume

Event outcomes

2

Family volume

$744K

Best sibling

Los Angeles L 23¢

Ticker

KXNBAGAME-26MAY09OKCLAL-OKC

Market snapshot

Oklahoma City in market context.

This page tracks the Kalshi contract for Game 3: Oklahoma City at Los Angeles L Winner?. The displayed quote is 77¢ from the latest venue quote. The cached market record reports 24h volume of $129K. In the Game 3: Oklahoma City at Los Angeles L Winner family, this outcome ranks #1 of 2 by current quote across 2 sibling outcomes. The indicator bundle was refreshed May 9, 2026, 5:53 AM UTC.

Outcome

Oklahoma City

Family rank

#1 of 2

Venue

Kalshi

Current quote

77¢

Quote source

Latest venue quote

Timing

Listed until May 24, 2026

24h volume

$129K

Family context

2 outcomes · Game 3: Oklahoma City at Los Angeles L Winner

Quote range

23¢-76¢

Family leader

Oklahoma City 76¢

Last updated

May 9, 2026, 5:53 AM UTC · 14m ago

Venue identifier: KXNBAGAME-26MAY09OKCLAL-OKC. Family volume: $744K.

Price history

77¢ current

+64¢
25¢50¢75¢100¢
May 3, 2026May 8, 2026

Orderbook snapshot

76 / 77¢

Kalshi
1¢ spread
BidSize
76¢16K
75¢38K
74¢38K
73¢14K
72¢3.9K
AskSize
77¢1.1M
78¢1.2M
79¢78K
80¢48K
81¢3.3K

Contract terms

Resolution, venue, and identifiers.

Resolution rules

If Oklahoma City wins the Game 3: Oklahoma City at Los Angeles L professional basketball game originally scheduled for May 9, 2026, then the market resolves to Yes.

Venue

Kalshi

Closes

May 24, 2026

Identifier

KXNBAGAME-26MAY09OKCLAL-OKC

Event family

Game 3: Oklahoma City at Los Angeles L Winner.

This view keeps the individual contract next to its sibling outcomes. For long-tail search traffic, this is the useful context: where the current price sits inside the event, how much volume exists around the family, and which outcomes have actual depth.

Total volume

$744K

Outcomes

2

Highest price

Oklahoma City 76¢

Current share

17%

Indicators

Yield, cliff risk, volatility, and regime.

IY (Yes)

780.1%

IY (No)

7822.9%

Adj IY

7720%

CRI

3

RV

112%

VR

0.41

Regime

neutral

Score

0.5

Full indicator table

780.1%
7822.9%
Adj IY
7720%
3
RV
112%
VR
0.41
IAR
0.5/h
LAS
0.01

Odds pages

Related prediction questions

Browse odds

Related readings

Matched from SimpleFunctions blog, opinions, technical guides, concepts, and learn pages.

Browse library
Opinioncomparison

Kalshi vs Polymarket: Mechanics, Fees, Regulation, Liquidity (2026)

Side-by-side comparison of Kalshi and Polymarket in 2026. Fee math, calibration data, withdrawal speed, and a decision tree for picking the right venue.

Blogmarkets

Kalshi vs Polymarket: Which Prediction Market Should You Trade?

In-depth comparison of Kalshi and Polymarket for prediction market traders. Regulatory structure, liquidity, fees, API tooling, and cross-venue trading with SimpleFunctions.

Technicalguide

Kalshi vs Polymarket: A Developer's Comparison of APIs, Orderbooks, and Liquidity

Data-driven comparison of Kalshi and Polymarket APIs, orderbooks, rate limits, and liquidity. Code examples for building on both prediction markets.

Opinionanalysis

Liquidity Availability Is the Real Edge in Prediction Markets

Implied yield, cliff risk, and overround all describe what to trade. Liquidity Availability Score describes whether the orderbook can absorb the trade. Why LAS is the indicator that decides who actually books P&L.

Blogmarkets

Prediction Market Orderbook Analysis: Reading Depth, Spread, and Liquidity

How to read prediction market orderbooks. Binary settlement, spread-as-percentage, depth asymmetry, executable edge calculation, and cross-venue arbitrage analysis.

Opinionanalysis

Implied Yield vs Raw Probability: Why Bond-Adjacent Prediction Markets Need a Different Lens

Why fixed-income-adjacent prediction-market contracts need to be priced in implied yield, not raw probability, with two real Kalshi Fed-decision contracts as a case study.

SimpleFunctions context

Index, screen, query, and monitor.

Open index