Prediction markets just printed a new weekly usage high with 38.01 million in volumes, led by Polymarket with 22.58 million and Kalshi with 14.86 million. Opinion comes in the third place with 227,500 weekly transactions, according to Dune.

Polymarket accounts for the majority of recorded trades, with Kalshi close behind. That concentration matters because prediction-market liquidity tends to pool where the most active markets live. When trade counts cluster on two venues, market makers have a simpler routing problem, spreads often tighten on the largest questions, and cross-market hedging becomes easier.

It also implies the sector has a “habit loop.” Prediction markets do not need every user to be a professional trader. They need repeated engagement on a small set of recurring event categories. When weekly trades stay elevated across multiple weeks, it usually signals repeat participation rather than a one-off novelty burst.

Why Trade Counts Matter, and Where They Can Mislead

High trade counts typically mean tighter feedback loops. More orders and fills improve price discovery, which makes the market more informative, which can attract more users and more makers. That flywheel is one reason “event markets” can scale quickly once a few categories become mainstream.

At the same time, trade count can overstate economic weight if the metric is counting micro-fills, partial fills, or internal settlement steps rather than unique user actions. Prediction markets can generate high transaction counts via small incremental position changes, automated strategies, or market-making adjustments.

This is why the definition of “trades” is the first verification step. The KuCoin and Odaily wording alternates between “transactions” and “trades.” In practical terms, the dataset may be counting fills, orders, or platform-specific transaction events. A single user could generate many “trades” without meaningfully increasing participation or liquidity.

Why It Matters

Sticky consumer behavior is rare in crypto-adjacent products. Prediction markets behave more like a consumer finance app than a typical token narrative. Users return when events keep happening and the interface makes it easy to express a view. Persistent high weekly trades suggest the product loop is working.

Liquidity providers follow activity. When market makers see consistent flow, they can justify tighter spreads and larger size because inventory turns faster. That can improve pricing, reduce slippage, and increase the amount of capital willing to quote event risk.

Concentration can become an advantage. If Polymarket and Kalshi continue to dominate the trade count, they can set de facto standards for contract design, resolution practices, and how markets handle edge cases. That reduces fragmentation, which historically has been a major friction for prediction markets.

Is This Spike Event-Driven or Structural

A single week record can come from one headline category. Elections, major sports runs, macro releases, and high-attention geopolitical events can all cause bursts. In that scenario, trade counts often snap back down after the event passes.

Structural growth looks different. It shows up as a higher baseline week after week, across multiple categories, with steady or rising active user counts. If the record is structural, it should also appear in other metrics like unique traders, total notional volume, and average market depth.

That is why trade count alone is best treated as a usage headline, not a proof of durable liquidity.

What This Suggests For The Sector

If prediction markets can sustain this trade tempo, the next phase likely looks less like a novelty product and more like a liquidity business. More flow attracts more makers, which tightens spreads, which improves the experience, which pulls in more users.

The constraints are also clear. Higher usage raises the stakes for resolution credibility, market integrity, and regulatory scrutiny. If the trade count keeps pushing new highs, the operational details that felt secondary during early growth can become the primary risk factors that decide whether liquidity stays.

The post Prediction Markets Quietly Set a Usage Record With 38.01M Weekly Trades appeared first on Crypto Adventure.

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Filed under: Bitcoin - @ February 23, 2026 10:12 am