There is a useful distinction between the categories where whales win most often and the categories where whales win the largest amounts. These two questions produce different answers. Frequency favors short-dated markets with efficient pricing, where the population- level win rate is high but the per-trade payout is modest. Size favors long-dated markets with extreme prices, where the population-level win rate is lower but the asymmetric payouts produce leaderboard-scale outcomes. This article focuses on the second question: where the biggest paying trades concentrate, why those categories produce outsized outcomes, and what the pattern implies for copy-traders who want exposure to the asymmetric upside.
The leaderboard, observed directly
The list below shows the largest paper-PnL gains on record across Polymarket and Kalshi. The figures are calculated under the assumption that each position was held to resolution at the recorded entry price.
- 1Will United States win on 2026-06-12?Polymarket·culture·stake $920K·@ 46¢+$1.1M
- 2Will IR Iran win on 2026-06-15?Polymarket·politics·stake $790.8K·@ 49¢+$823.1K
- 3Will Spain win on 2026-06-15?Polymarket·culture·stake $78.6K·@ 9¢+$794.4K
- 4Will Spain win on 2026-06-15?Polymarket·culture·stake $47.4K·@ 9¢+$479.4K
- 5UFC 328: Sean Strickland vs. Khamzat Chimaev (Middleweight, Main Card)Polymarket·sports·stake $103.6K·@ 19¢+$441.8K
- 6Will Canada win on 2026-06-18?Polymarket·culture·stake $1.3M·@ 76¢+$420.1K
- 7What will the announcers say during Jordan vs Argentina?Kalshi·culture·stake $4.1K·@ 1¢+$407.0K
- 8Spread: Spain (-2.5)Polymarket·culture·stake $345K·@ 46¢+$405K
- 9Spurs vs. ThunderPolymarket·sports·stake $198K·@ 33¢+$402K
- 10Roland Garros ATP: Jakub Mensik vs Andrey RublevPolymarket·sports·stake $370.0K·@ 48¢+$400.8K
What the leaderboard reveals
The structural pattern is consistent across the top of the list. The largest paying trades are almost uniformly entries at prices well below 0.30 on contracts that eventually resolved YES, or entries above 0.70 on contracts that eventually resolved NO. The pattern is not coincidental; it is a direct consequence of the payout structure of prediction-market contracts.
A contract priced at 0.10 pays $1.00 on a YES resolution. A trader who deploys $50,000 at that price owns 500,000 contracts, which pay $500,000 in aggregate if the contract resolves correctly. The profit is $450,000 on the $50,000 entry, a payout ratio of nine to one. The same trader deploying $50,000 at 0.50 produces a payout of $50,000 in profit, a one-to-one return. The arithmetic favors low-probability entries when the trader's read is correct, and the leaderboard reflects exactly this asymmetry.
The corresponding implication is that a copy-trader who focuses exclusively on near-coinflip positions will rarely produce trades that appear on a leaderboard like this one, even with a perfect win rate. The mathematics simply do not support large absolute payouts on tightly priced contracts; the only way to produce a five-figure or six-figure profit on a single trade is to take a price that almost nobody else believed in, and to be correct.
Why politics and crypto dominate the top of the list
The categorical concentration on the leaderboard is almost entirely political and crypto contracts, with the occasional macro and sports entry at lower ranks. The concentration has two structural causes.
The first is contract duration. Political and crypto contracts often resolve months or longer after entry, which allows the underlying probability to sit at extreme prices for extended periods. A trader who identifies a contract that the market has materially mispriced can accumulate a large position at the favorable price over multiple weeks, rather than being forced to take the available size in a single execution. The depth of the position at resolution determines the payout, and the duration of the favorable price determines how much depth was achievable.
The second is the breadth of plausible outcomes. Sports contracts typically resolve into one of a small number of clearly defined outcomes, and the prices on each outcome are tightly pinned by the modeling work that professional bettors apply. Political contracts can resolve into outcomes that the broader market did not fully anticipate, particularly on long-tail candidates or unusual structural events. The wider distribution of possible outcomes creates more opportunities for the market to be wrong by a wide margin.
Crypto contracts share some of the structural characteristics of political contracts: long durations, wide distributions of possible outcomes, and discrete catalyst events that can produce large price gaps. The leaderboard contribution from crypto is smaller than from politics but follows the same pattern of asymmetric payouts on extreme-price entries that resolved correctly.
Why sports rarely produces leaderboard entries
Sports contracts have higher population-level win rates than political or crypto contracts, but they almost never produce single-trade payouts of leaderboard magnitude. The reason is the efficiency of the underlying pricing. Sports prediction-market contracts compete with offshore sportsbooks for liquidity, and the prices on major leagues are quoted within a few cents of each other across venues. A contract priced at 0.45 is rarely available for accumulation at 0.10; the price simply does not sit at extremes long enough for a trader to load up before the broader market corrects.
The result is that sports betting on prediction markets produces steady, replicable wins with modest per-trade payouts. The category is appropriate for copy-traders who are optimizing for compounding rather than for catching the occasional large trade. It is not the category where leaderboard entries are made.
The trade-off between frequency and magnitude
Different copy-traders should optimize for different outcomes. A trader who is comfortable with positions that resolve within days, who has access to attention for managing close-of-day mechanics, and who is satisfied with moderate compounding should weight sports and macro contracts heavily. A trader who is comfortable holding for months, who has the temperament to ride through adverse price action, and who is targeting the occasional large win should weight political and crypto contracts.
Many serious copy-traders run a mixed portfolio. A core position in short-dated categories produces the steady cash flow that funds continued participation, while a smaller allocation to long-dated categories provides exposure to the asymmetric upside that produces the occasional large outcome. The mix is deliberate; it is not the result of opportunistic position-taking across whatever the daily feed surfaces.
What the leaderboard implies for copy-trading discipline
The structural lesson of the leaderboard is that copy-trading the trades that eventually produce large payouts requires the willingness to take positions that, at the moment of entry, look uncomfortable. A contract priced at 0.10 looks like a clear loser at the moment of the trade, because the market is pricing it as a 10 percent event. The copy-trader who rides along is taking the side of the book that the market has rejected. The trades that pay are the trades where the rejection was wrong.
Most retail copy-traders cannot sustain this discomfort. The intuitive gravitational pull is toward favorites, which feel safer in the moment but produce the smallest payouts on the leaderboard. Adjusting toward contested-price entries, with proper sizing and attention to wallet history, is the discipline that the leaderboard rewards. The framework is set out in more detail in our guide to copy-trading, with the supporting evidence on whale profitability in our analysis of whether whales are actually profitable.
Frequently asked questions
What was the largest single whale trade on record?
The largest documented single-position whale gain in the Rivo dataset exceeded $80 million across a small cluster of correlated political contracts during the 2024 U.S. election cycle. The same wallet produced multiple eight-figure trades on adjacent contracts. The aggregate position was the largest concentrated political bet ever placed on a prediction market.
How often do leaderboard-scale trades occur?
Rarely. The leaderboard is dominated by the largest outcomes from a population of millions of trades. A copy-trader following a focused set of wallets across a year will typically see a small number of trades with payouts in the high five or low six figures, and only the occasional trade above that level. Setting expectations against the leaderboard, rather than against typical category-level returns, produces unrealistic targets.
Is the leaderboard biased by survivorship?
Yes. The leaderboard surfaces the trades that paid. The corresponding population of losing positions on the same categories is much larger. Reading the wins leaderboard in isolation produces an overoptimistic view of category outcomes. The losses leaderboard, published alongside, provides the corrective view and is described in our biggest losses article.
Which platform produces more leaderboard entries?
Polymarket, by a wide margin. The combination of deeper political-contract liquidity and longer holding periods on the platform produces more of the outcomes that appear on the wins leaderboard. Kalshi appears on the leaderboard primarily in macro and sports categories at lower ranks.
Can I expect copy-trading to produce a leaderboard outcome?
Realistically, no. The defensible expectation for a disciplined copy-trader is moderate compounding with the occasional larger trade. Trades of leaderboard magnitude require both an aggressive position size and a correct read on an extreme-price contract that resolves correctly, a combination that does not replicate at scale across a copy-trading strategy.