The term whale is used loosely across crypto, sports betting, and prediction markets, often to describe any wallet with an unusually large position. This article sets out the more precise definition Rivo uses for the term in the prediction-market context, the thresholds that separate whales from market makers and from retail traders, and the framework for evaluating whether a given whale-sized trade carries directional signal.
The working definition
A whale, in the Rivo dataset, is a wallet that places a single large opening position on a Polymarket or Kalshi event contract. The threshold is chosen because below that level the population of traders is dominated by behavior that does not reliably carry directional information, while above that level the population thins out to participants who have made an active decision to deploy capital against a specific view.
The definition has three deliberate components. The first is the size floor, an internal threshold large enough to filter out small-scale activity. The second is the requirement that the position be an opening rather than a close; a large sell on a previously entered position is a paper gain being realized, not a fresh directional view. The third is the per-contract framing; a trader who spreads a large total across ten small positions is operating differently from a trader who places a single large ticket on one contract, and the second behavior is the one the whale definition is meant to capture.
Why a size threshold is the right filter
The argument for using size as the primary filter on prediction-market activity rests on the structural differences between large and small participants. Below the threshold, three populations dominate the trade flow: retail traders copying other retail traders, market makers placing inventory-management trades, and small-scale arbitrage bots running price discovery between related contracts or between platforms. None of these three populations carries directional information, and each can produce large volumes of activity that looks superficially similar to whale flow.
Above the threshold the picture changes. Retail traders rarely take single positions at that size because the position represents a meaningful share of a typical retail bankroll. Market makers occasionally place large single-sided positions, but the pattern is identifiable through the round-trip activity that follows. Arbitrage bots almost never operate at this size because the spreads on prediction markets are not wide enough to support the inventory cost. What remains, after these populations are filtered, is a smaller and more concentrated set of traders making deliberate directional bets. The threshold is the simplest filter that produces a clean enough sample to study.
Whales versus market makers
Market makers and whales look superficially similar in raw trade volume but operate on opposite premises. A market maker is in the business of providing liquidity. They quote both sides of the book, collect the spread, and aim for a flat directional exposure across the trading day. Their large trades are inventory adjustments, not directional views. Copy-trading a market maker is the equivalent of subscribing to their inventory schedule, and it produces a portfolio that looks like the residual of their hedging activity, not a portfolio of high-conviction positions.
A whale is taking a side. The transaction is asymmetric from their point of view: they want to own YES at 0.34 because they believe the contract is mispriced, and they do not plan to immediately reverse the position to capture a few cents of spread. The holding pattern of a whale is in days or weeks, not minutes or hours. The exit is at resolution or at a price that reflects a material change in the underlying probability, not at a small spread above entry.
Rivo applies several heuristics to filter market-making activity out of the whale feed. Wallets that round-trip the same contract within minutes are deprioritized; wallets that quote both sides of a market actively are flagged; very short holding times correlated with two-sided activity are excluded from directional whale statistics. The goal is to produce a feed that reflects directional conviction rather than the underlying liquidity provision that keeps the platforms functioning.
Identity whales versus behavioral whales
There are two ways to classify a trader as a whale. The first is by identity: the wallet is known, the resolved history is documented, and the trader has a track record that informs the weight a copy-trader places on each new trade. The second is by behavior: the wallet is new or previously unobserved, but the size and pattern of the current activity is consistent with whale operation.
Identity whales are the more useful population for copy-trading because the resolved history allows weighting by skill rather than by size alone. A wallet with two hundred resolved positions and a positive PnL in political markets carries different signal from a wallet making its first six-figure position on a political contract, even if both trades look identical in the raw tape.
Behavioral whales are valuable for a different reason: they catch new entrants into the market who would otherwise be unobservable. A previously unknown wallet placing a series of large coordinated bets on a specific outcome is worth noting, even before the resolved history accumulates, because the pattern itself contains information about how capital is being deployed in the market.
What whale activity does not imply
Several inferences are commonly drawn from whale activity that are not supported by the underlying data.
The first is the claim that whales are necessarily informed in a privileged sense. The phrase "smart money" suggests inside knowledge, but the typical whale on Polymarket or Kalshi is operating from the same publicly available information that a retail trader could access. The edge is analytical rather than informational. A whale who consistently outperforms is doing so by drawing different conclusions from the same data, not by possessing data that other participants lack.
The second is the claim that any large bet from a wealthy individual constitutes a whale signal. Capital alone does not produce edge. Wealthy individuals who place whale-sized bets on prediction markets are no more likely to be correct on the underlying outcome than any other participant of comparable analytical sophistication. The whale label, applied to a wallet with no resolved history, is a description of capital deployment and not a prediction of outcome.
The third is the claim that whale activity reliably moves the market in the whale's direction over the medium term. Some trades do move the market; many do not. A whale buying YES at 0.34 may push the price to 0.36 immediately, but the price three days later is determined by subsequent flow, not by the whale's entry. Copy-traders who assume the whale's trade is the start of a sustained move are frequently wrong.
Reading whale signal correctly
The productive use of the whale label is as a noise filter, not as a verdict. Whale activity surfaces the population of trades worth examining more carefully. The work of evaluating whether any specific whale trade is worth copying is downstream of the filter. The framework Rivo uses elsewhere on the site, covering wallet history, category fit, entry price, and book depth, is the downstream evaluation. The whale label is the entry criterion.
For a more detailed treatment of how to act on whale activity, see our guide to copy-trading. For a discussion of whether bigger tickets correspond to better trades, see does a bigger bet mean a smarter bet.
Frequently asked questions
What is the minimum trade size that qualifies as a whale trade?
Rivo applies an internal size floor for single-contract opening positions. The threshold is chosen to filter out retail-scale activity, market-maker rebalancing, and small arbitrage flow. Different publishers use different thresholds; the practical takeaway is that any threshold large enough to exclude retail activity produces a similar population of trades.
Are all whales profitable?
No. Size is a description of how much capital a trader is deploying, not a description of how well they are using it. The resolved-history filter is what separates the population of profitable whales from the population of whales who happen to be large. A copy-trader should weight by resolved PnL rather than by current ticket size.
Can the same wallet be a whale on both Polymarket and Kalshi?
In principle yes, but the platforms have different identity models. Polymarket wallets are pseudonymous and identifiable by on-chain address. Kalshi accounts require real-name KYC and are not publicly identifiable. Some traders appear to operate on both platforms with correlated patterns, but the cross-platform identity link is rarely provable.
How does a whale on a prediction market differ from a whale on a crypto exchange?
On a spot or derivatives exchange, large positions can reflect a wide variety of activity, including indexing, hedging, and treasury management. On a prediction market, the structure of the contract limits whale activity to directional bets on a binary outcome. A whale on Polymarket or Kalshi is, almost by construction, a directional trader. That is part of why the whale signal is more interpretable on prediction markets than on most other venues.
Do whales coordinate?
Occasionally. Coordinated whale activity is visible when multiple wallets accumulate the same position over a short window. More often, large traders are operating independently from the same publicly available data, which produces correlated activity without explicit coordination. Distinguishing the two is hard from the trade tape alone.