SimpleFunctions
KalshiOct 7, 2026151 days left

Will the Golden State Valkyries Women's Pro Basketball team win at least 15 games this season?

This contract is priced at 94¢ midpoint on Kalshi. Current book: 88¢ bid, 99¢ ask, 11¢ spread.

Implied probability

94¢
$0 volume
1.3 LAS liquidity
0% of event volume

Event outcomes

7

Family volume

$146

Best sibling

25+ wins 21¢

Ticker

KXWNBAWINS-26GS-15

Market snapshot

15+ wins in market context.

This page tracks the Kalshi contract for Will the Golden State Valkyries Women's Pro Basketball team win at least 15 games this season?. The displayed quote is 94¢ from the visible bid/ask midpoint because the last venue price is zero. In the Will the Golden State Valkyries Women's Pro Basketball team win at least family, this outcome ranks #2 of 7 by current quote across 7 sibling outcomes. The indicator bundle was refreshed May 9, 2026, 12:08 PM UTC.

Outcome

15+ wins

Family rank

#2 of 7

Venue

Kalshi

Current quote

94¢

Quote source

Bid/ask midpoint

Timing

Listed until Oct 7, 2026

Reported volume

Family context

7 outcomes · Will the Golden State Valkyries Women's Pro Basketball team win at least

Quote range

2¢-90¢

Family leader

10+ wins 90¢

Last updated

May 9, 2026, 12:08 PM UTC · 9m ago

Venue identifier: KXWNBAWINS-26GS-15. Family volume: $146.

Price history

94¢ current

+92¢
25¢50¢75¢100¢
May 6, 2026May 9, 2026

Orderbook snapshot

88 / 99¢

Kalshi
11¢ spread
BidSize
100¢50
88¢355
86¢350
5¢5.0K
AskSize
99¢400

Contract terms

Resolution, venue, and identifiers.

Resolution rules

If the Golden State Valkyries Women's Pro Basketball team wins at least 15 games in the 2026 regular season, then the market resolves to Yes.

Venue

Kalshi

Closes

Oct 7, 2026

Identifier

KXWNBAWINS-26GS-15

Event family

Will the Golden State Valkyries Women's Pro Basketball team win at least.

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

$146

Outcomes

7

Highest price

10+ wins 90¢

Current share

0%

Indicators

Yield, cliff risk, volatility, and regime.

IY (Yes)

32.9%

IY (No)

1771.7%

Adj IY

1570%

CRI

7

RV

1568%

VR

22.73

Regime

neutral

Score

0.5

Full indicator table

32.9%
1771.7%
Adj IY
1570%
7
RV
1568%
VR
22.73
IAR
0.3/h
Overround
1.7%
LAS
0.11

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.

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.

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.

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