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Observed Kalshi and Polymarket whale outcomes

Every whale-lane trade Rivo recorded on Kalshi and Polymarket from September 10, 2026 to October 10, 2026, and how the recorded buys settled at a fixed $100 stake. Frozen at export; downloadable as JSON and CSV.

See the resultsDownload JSON

Exported October 10, 2026. Method observed-buy-events-v1.

Recorded whale trades
319,860

Both venues, whale lane only, in the observation window.

Distinct markets
63,361

Markets with at least one recorded whale trade.

Settled buys scored
242,447

Eligible buys with a win or loss observed at export.

Combined win rate
64.9%

Wins over settled buys, both venues pooled. See each venue below.

Results by venue

Read each column as its own sample. The venues are collected differently and carry different size floors, so the table is two studies side by side rather than a contest.

Kalshi

107,722 trades
Win rate
74.4%

45,198 wins, 15,563 losses

Gross PnL
-$98,779

on $6,076,100 staked

Return on stake
-1.6%

-$1.63 per settled buy

Still open at export
3.3%

2,071 unresolved buys

Polymarket

212,138 trades
Win rate
61.8%

112,222 wins, 69,464 losses

Gross PnL
-$150,260

on $18,168,600 staked

Return on stake
-0.8%

-$0.83 per settled buy

Still open at export
6.4%

12,509 unresolved buys

Window ends 2026-10-10 at 00:00 UTC. Unresolved and void buys are excluded from win rate, stake and PnL. Sells are recorded in the trade count but never scored.
MeasureKalshiPolymarket
Recorded whale trades107,722212,138
Distinct markets48,80814,553
Trades per market2.214.6
Identified traders10,8016,314
Buy trades62,885194,969
Eligible buys settled60,761181,686
Wins45,198112,222
Losses15,56369,464
Win rate on settled buys74.4%61.8%
Stake deployed at $100 per buy$6,076,100$18,168,600
Gross paper PnL-$98,779.18-$150,260.41
Return on stake-1.63%-0.83%
PnL per settled buy-$1.63-$0.83
Unresolved eligible buys2,07112,509
Void eligible buys53774
Invalid prices, all trades00
Unknown position change, all trades107,7223,413

Reading the result

Read each venue on its own terms. On Kalshi, 60,761 settled whale buys won 74.4% of the time and returned -1.6% on stake gross, across 48,808 markets at about 2.2 trades per market. On Polymarket, 181,686 settled whale buys won 61.8% of the time and returned -0.8% on stake gross, across 14,553 markets at about 14.6 trades per market.

A win rate says nothing on its own about return, because the entry price sets the payoff. Trades per market says how correlated the sample is: many buys in one market are many rows and one outcome. The unresolved share says how recent the tail is. Use the backtester to slice the same events by price band, size, category and trader rather than reading the pooled figure as a strategy.

Population and method

  • Window. Detection time from 2026-09-10T00:00:00.000Z inclusive to 2026-10-10T00:00:00.000Z exclusive.
  • Lane. Whale lane only: trades above each venue's size floor, whoever placed them. Tracked-lane trades by identified traders below the floor are excluded.
  • Eligibility. buy_yes and buy_no with a recorded price strictly between 0 and 1. Invalid prices are counted and excluded.
  • Scoring. Resolution observed at export time: win, loss, void or unresolved. Only wins and losses enter the rate and the PnL.
  • Stake. $100 per eligible settled buy, filled at the recorded price, held to settlement. PnL is 100 / price − 100 on a win and −100 on a loss.
  • Not modelled. Fees, spread, slippage, entry delay, partial fills, depth, position limits, capital lock-up, and correlation between trades in the same market.
  • Categories. Reported as unknown because labels were not verified for research use at export. No category claim is made.
  • Export. One read-only, repeatable-read transaction against the production history, so every count comes from the same instant.

The full definitions, including the settlement rule and the payoff arithmetic, are on the methodology page.

Downloads and provenance

Both files are free to reuse with attribution. The JSON is the manifest; the CSV is the table above.

JSON
Snapshot manifest

Window, method, stake, per-venue buckets, content hash.

CSV
Aggregate table

One row per venue bucket, every column in the results table.

The source revision is the repository commit the export ran against. The content hash is computed over the manifest with the hash field removed, and the page refuses to render a file whose hash does not match.
FieldValue
Study slugobserved-whale-outcomes-2026-10-10
Method versionobserved-buy-events-v1
Generated at2026-10-10T21:17:30.936Z
Observation window2026-09-10T00:00:00.000Z to 2026-10-10T00:00:00.000Z (end exclusive)
Fixed stake$100 per eligible settled buy
Categories verifiedNo, reported as unknown
Source revisiondf024040c6ccd78f092f1cfb2059da7b97d3cd0a
Content SHA-25672bb0c4d859af66edeff79320947e08371f13386f800a39609c591a4a1336067
Cite this study
Rivo (2026). Observed Kalshi and Polymarket whale outcomes. Observation window 2026-09-10 to 2026-10-10 (UTC, end exclusive), exported 2026-10-10. Method observed-buy-events-v1, $100 fixed stake per eligible recorded buy, gross paper PnL. https://rivo.markets/research/observed-whale-outcomes-2026-10-10

Frequently asked questions

What population does this study cover?

Whale-lane trades on Kalshi and Polymarket detected from September 10, 2026 inclusive to October 10, 2026 exclusive, UTC. Tracked-lane trades (identified traders below the size floor) are excluded. It is the activity Rivo's collectors recorded in that window, not all trading on either venue.

Which trades were scored?

Recorded buy_yes and buy_no trades with a price strictly between zero and one, using the market resolution observed at export time. Sells are recorded but never scored, so every rate here is a rate on buys. Void markets are counted and excluded; unresolved buys are counted and excluded.

What does gross hypothetical PnL mean?

Each eligible settled buy is treated as a $100 stake filled at the recorded price and held to settlement: a win returns 100 / price minus 100, a loss returns minus 100. Fees, spread, slippage, entry delay, partial fills and capital limits are not modelled. It is a description of the tape, not of any account.

Why are categories reported as unknown?

Category labels for this window had not been verified for research use at export, so the study reports one bucket per venue and makes no category claim. A later study may add verified categories; this one will not be edited.

Why is every Kalshi trade an unknown position change?

Kalshi exposes direction and size but not the trader's existing position, so open, add, trim and close cannot be distinguished. Polymarket positions are read on chain, which is why most Polymarket trades are classified.

Does this show that one venue is better than the other?

No. The two venues are collected through different pipelines with different size floors and identity models, so the columns describe two populations. Compare each venue with its own earlier studies rather than with the other column.

Can I reproduce it?

The JSON manifest carries the window, method version, stake, source revision and a SHA-256 over the payload. The underlying events are queryable through the API and MCP server. Re-running the same window later will differ because settlements continue to arrive; that is a new study, not a correction.

Slice the same history yourself.

Filter these events by venue, price band, size, category and trader in the terminal, or ask Claude to do it through the MCP server, with an out-of-sample holdout on every rule.

Get access

Related

  • Methodology
    How Rivo records trades, settles markets, computes paper PnL, grades traders and validates rules.
  • Kalshi whale tracker
    Live large trades on Kalshi with the trader, market, side, size, and entry price attached.
  • Polymarket whale tracker
    Real-time whale trades on Polymarket with resolved PnL and wallet history.
  • Backtesting
    Score a trader or a signal against resolved Polymarket and Kalshi markets before the bot runs.
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