Artist with the most monthly Spotify listeners at the end of May 2026
Bruno Mars is priced at 88¢ on Kalshi. Current book: 88¢ bid, 89¢ ask, 1¢ spread. This outcome ranks #1 of 12 inside Artist with the most monthly Spotify listeners at the end of May 2026.
Price history
88¢ current
+67¢Contract brief
If the artist with the most monthly listeners on Spotify on May 31, 2026 at 12:00 PM ET is Bruno Mars, then the market resolves to Yes.
Outcome
Bruno Mars
Rank
#1 of 12
Leader
Bruno Mars 88¢
Range
1¢-88¢
Family volume
$65K
Identifier
KXTOPMONTHLY-26MAY-BRU
May 27, 2026, 12:38 AM UTC · 26m ago
Implied probability
Bid
88¢
Ask
89¢
Spread
1¢
24h volume
$13K
Family rank
#1 of 12
12 outcomes · Artist with the most monthly Spotify listeners at the end of May 2026
Closes
May 31, 2026
Family volume
$65K
Orderbook snapshot
88 / 89¢
Contract terms
What resolves this market.
YES condition
If the artist with the most monthly listeners on Spotify on May 31, 2026 at 12:00 PM ET is Bruno Mars, then the market resolves to Yes.
Venue
Kalshi
Closes
May 31, 2026
Identifier
KXTOPMONTHLY-26MAY-BRU
Event family
Artist with the most monthly Spotify listeners at the end of May 2026.
The same race as a probability stack: rank, volume, and where this contract sits against the other outcomes.
Total volume
$65K
Outcomes
12
Highest price
Bruno Mars 88¢
Current share
21%
Bruno Mars
kalshi · KXTOPMONTHLY-26MAY-BRU
Justin Bieber
kalshi · KXTOPMONTHLY-26MAY-JUS
Drake
kalshi · KXTOPMONTHLY-26MAY-DRA
Taylor Swift
kalshi · KXTOPMONTHLY-26MAY-TAY
Ariana Grande
kalshi · KXTOPMONTHLY-26MAY-ARI
Kendrick Lamar
kalshi · KXTOPMONTHLY-26MAY-KEN
The Weeknd
kalshi · KXTOPMONTHLY-26MAY-WEE
Bad Bunny
kalshi · KXTOPMONTHLY-26MAY-BAD
Billie Eilish
kalshi · KXTOPMONTHLY-26MAY-BIL
Ed Sheeran
kalshi · KXTOPMONTHLY-26MAY-ED
Lady Gaga
kalshi · KXTOPMONTHLY-26MAY-LAD
Rihanna
kalshi · KXTOPMONTHLY-26MAY-RIH
Indicators
Yield, cliff risk, volatility, and regime.
Regime
neutral
Score
0.5
Full indicator table
Odds pages
Related prediction questions
Related readings
Matched from SimpleFunctions blog, opinions, technical guides, concepts, and learn pages.
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.
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.
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.
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.
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.
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.
Prediction Market Index
Market-wide volatility, geo risk, breadth, and activity around this contract.
Market Screener
Filter adjacent contracts by volume, expiry, IY, CRI, venue, and theme.
Event Probability API
Read 88% as a structured event probability object for agents and apps.
Realtime Data API
Prices, orderbooks, movement, heat, and liquidity indicators across venues.
World State API
Compact market-aware context packets for agent sessions and scheduled refresh.
Hedging Workflows
Map a thesis or exposure to candidate event markets and monitoring paths.
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.