SimpleFunctions

Alexander Zverev wins for French Open Men's Singles

Alexander Zverev wins: Alexander Zverev is priced at 7¢ on Kalshi. Current book: 7¢ bid, 20¢ ask, 13¢ spread. This outcome ranks #3 of 11 inside French Open Men's Singles.

Price history

7¢ current

5¢10¢
Sep 20, 2026Sep 20, 2026

Contract brief

If Alexander Zverev wins the 2027 French Open Men's Singles professional tennis tournament, then the market resolves to Yes.

Outcome

Alexander Zverev wins: Alexander Zverev

Rank

#3 of 11

Leader

Jannik Sinner wins: Jannik Sinner 40¢

Range

1¢-40¢

Family volume

$60

Identifier

KXATP-27FO-ZVE

Sep 20, 2026, 1:38 PM UTC · 17m ago

Implied probability

7¢
Latest venue quote
Sep 20, 2026, 1:38 PM UTC · 17m ago

Bid

7¢

Ask

20¢

Spread

13¢

Reported volume

$2

Family rank

#3 of 11

11 outcomes · French Open Men's Singles

Closes

Jun 29, 2027

Family volume

$60

Orderbook snapshot

7 / 20¢

Kalshi
13¢ spread
BidSize
100¢90
7¢198
AskSize
20¢200
26¢90
46¢500
47¢5.0K
50¢1.1K

Contract terms

What resolves this market.

YES condition

If Alexander Zverev wins the 2027 French Open Men's Singles professional tennis tournament, then the market resolves to Yes.

Venue

Kalshi

Closes

Jun 29, 2027

Identifier

KXATP-27FO-ZVE

SF Signal
SF Index
861.28
Regime
neutral

Indicators

Yield, cliff risk, volatility, and regime.

IY (Yes)

1722.6%

IY (No)

9.8%

Adj IY

861%

CRI

13

Overround

-0.1%

Regime

neutral

Score

0.5

Full indicator table

1722.6%
9.8%
Adj IY
861%
13
Overround
-0.1%

Related readings

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

Browse library
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.

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

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

How we compute these odds

SimpleFunctions aggregates live prediction-market contracts from Kalshi and Polymarket. Each slug groups contracts that resolve on the same underlying event, identified by venue event_id.

For binary slugs, the headline probability is the liquidity-weighted mid-price across all bound contracts. For multi-outcome slugs (e.g. elections with 3+ candidates), the headline is the leader’s price; we never arithmetically average disjoint outcomes — that would produce a number with no real-world meaning.

Snapshots refresh every 5 minutes during market hours; daily aggregates are computed at 04:00 UTC. The 30-day sparkline is drawn from per-ticker daily means stored in market_indicator_daily; 24h delta and movement events are derived from the same source.