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Research study, 30 days

Observed Kalshi and Polymarket whale outcomes

Every whale-lane trade Rivo recorded on Kalshi and Polymarket from August 14, 2026 to September 13, 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 September 14, 2026. Method observed-buy-events-v1.

Recorded whale trades
182,259

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

Distinct markets
22,057

Markets with at least one recorded whale trade.

Settled buys scored
134,705

Eligible buys with a win or loss observed at export.

Combined win rate
62.2%

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

19,922 trades
Win rate
77.3%

7,781 wins, 2,280 losses

Gross PnL
+$242,597

on $1,006,100 staked

Return on stake
+24.1%

+$24.11 per settled buy

Still open at export
16.8%

2,036 unresolved buys

Polymarket

162,337 trades
Win rate
61.0%

76,060 wins, 48,584 losses

Gross PnL
-$21,535

on $12,464,400 staked

Return on stake
-0.2%

-$0.17 per settled buy

Still open at export
15.4%

22,867 unresolved buys

Window ends 2026-09-13 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 trades19,922162,337
Distinct markets10,80211,255
Trades per market1.814.4
Identified traders2,9214,992
Buy trades12,103148,010
Eligible buys settled10,061124,644
Wins7,78176,060
Losses2,28048,584
Win rate on settled buys77.3%61.0%
Stake deployed at $100 per buy$1,006,100$12,464,400
Gross paper PnL+$242,597.06-$21,534.80
Return on stake24.11%-0.17%
PnL per settled buy+$24.11-$0.17
Unresolved eligible buys2,03622,867
Void eligible buys6499
Invalid prices, all trades00
Unknown position change, all trades19,9222,806

Reading the result

The headline numbers point in different directions, and both are worth taking at face value for what they describe. On Kalshi, 10,061 settled whale buys won 77.3 percent of the time and returned 24.1 percent on stake gross: $242,597 on $1,006,100 staked. On Polymarket, 124,644 settled whale buys won 61.0 percent of the time and returned minus 0.17 percent on stake: the pooled whale trade on Polymarket in this window was, before costs, a coin flip with a very large sample. That gap is the difference between a win rate and a return. A win at a high price pays little, and Polymarket whales in this window were paying up.

Trades per market is the number to hold onto. Kalshi recorded about 1.8 whale trades per market against 14.4 on Polymarket. Ten buys in one market are ten rows and one outcome, so the Polymarket sample has far fewer independent bets than its 162,337 rows suggest, in either direction. Its 22,867 unresolved buys, 15.5 percent of the eligible set, also show how recent the tail is: a window ending the day before export has many open positions, and the settled sample leans toward markets that resolve quickly, such as sports and short-dated crypto.

None of this is a recommendation to copy the average whale on either venue, and the two pipelines do not record the same population: Kalshi identity is only available where a trader shares a public name, and its whale floor differs from Polymarket's. The useful conclusion is narrower. Whale size alone is not a strategy on Polymarket, and the edge, where it exists, lives in subsets: a price band, a category, a trader with a graded record. That is what the backtester and ranked traders are for, and the events behind this study are the ones they run on.

Population and method

  • Window. Detection time from 2026-08-14T00:00:00.000Z inclusive to 2026-09-13T00:00:00.000Z 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-2026-09-13
Method versionobserved-buy-events-v1
Generated at2026-09-14T04:30:41.176Z
Observation window2026-08-14T00:00:00.000Z to 2026-09-13T00:00:00.000Z (end exclusive)
Fixed stake$100 per eligible settled buy
Categories verifiedNo, reported as unknown
Source revisiona0a4fee051f181e3568fc8e76663ab38c86c1758
Content SHA-2567b215b28858e27ae38c6fd15cb3a58458cb6367b45e1841d91b08d986d2997be
Cite this study
Rivo (2026). Observed Kalshi and Polymarket whale outcomes. Observation window 2026-08-14 to 2026-09-13 (UTC, end exclusive), exported 2026-09-14. Method observed-buy-events-v1, $100 fixed stake per eligible recorded buy, gross paper PnL. https://rivo.markets/research/observed-whale-outcomes-2026-09-13

Frequently asked questions

What population does this study cover?

Whale-lane trades on Kalshi and Polymarket detected from August 14, 2026 inclusive to September 13, 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.

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Related

  • Methodology
    How Rivo records trades, settles markets, computes paper PnL, grades traders and validates rules.
  • Kalshi whale tracker
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  • Polymarket whale tracker
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  • Strategy backtesting
    Score a rule against resolved Polymarket and Kalshi markets before you follow it.
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