Polymarket Trader Nets $233K on XRP Bet by Exploiting Weekend Liquidity

What to Know

• A Polymarket trader reportedly earned around $233,000 by exploiting thin weekend liquidity and automated market-making bots tied to an XRP prediction market.
• The strategy involved aggressively buying “UP” shares on Polymarket before executing a large XRP purchase on Binance minutes before contract settlement.
• The incident exposed weaknesses in prediction-market bots and sparked debate over market integrity, manipulation, and regulatory oversight.

Trader Exploits Quiet Weekend Conditions

A pseudonymous trader has drawn widespread attention after reportedly extracting approximately $233,000 in profits from XRP-related prediction markets on Polymarket during a low-liquidity weekend session. The episode unfolded late Saturday, a period when crypto trading volumes typically thin out, allowing relatively small capital moves to have an outsized market impact.

Market participants and analysts quickly debated whether the maneuver represented sharp trading or crossed into outright manipulation, reigniting broader concerns around prediction markets, automated bots, and safeguards during off-peak trading hours.

How the Strategy Played Out

According to details shared publicly by pseudonymous trader PredictTrader on X, the individual behind the trade operated under the wallet name @a4385. The trader began by aggressively accumulating “UP” shares in a Polymarket contract tied to XRP’s price direction over a short intraday window on January 17.

As buying pressure intensified, the price of UP shares climbed toward 70 cents, even as XRP’s spot price across major exchanges drifted lower by roughly 0.3%. This divergence triggered Polymarket’s automated market-making bots to respond mechanically, selling additional UP shares as prices rose.

By the time the market neared settlement, the trader had reportedly amassed around 77,000 UP shares at an average price close to 48 cents.

The Last-Minute XRP Purchase

Moments before the prediction market closed, the strategy escalated. Roughly two minutes ahead of settlement, a Binance wallet allegedly linked to the trader executed a $1 million XRP purchase. The trade pushed XRP’s spot price higher by an estimated 0.5% within minutes.

That brief price spike proved sufficient to tilt the outcome of the Polymarket contract in favor of the “UP” position. As a result, the UP shares settled at $1, generating a significant profit relative to the trader’s average entry price.

Shortly after settlement, the XRP position was reportedly unwound, sending the spot price lower once again. According to data circulated by PolymarketHistory, the entire operation cost the trader roughly $6,200 while inflicting heavy losses on liquidity-providing bots.

Bots Struggle to Adapt

The trader reportedly repeated similar tactics across multiple thinly traded weekend markets, systematically draining liquidity from automated bots. Some bots adjusted and exited markets, while others continued trading and absorbed losses.

The episode highlighted a structural weakness in many automated market-making systems. These bots typically treat all price movements equally, without factoring in time-of-day effects, liquidity conditions, settlement proximity, or adversarial trading behavior.

As a result, bots may continue providing liquidity even when market conditions become unfavorable or easily exploitable.

Calls for Smarter Algorithms

Industry participants argue the incident underscores the need for more sophisticated, context-aware bots. Such systems would dynamically adjust risk exposure based on volume, volatility, settlement timing, and counterparty behavior rather than reacting mechanically to price ticks alone.

Without smarter safeguards, critics warn prediction markets may struggle to attract institutional participation or maintain long-term credibility.

Market Integrity Concerns Grow

Chris Tremulis, global head of commodities compliance at Goldman Sachs, weighed in publicly, emphasizing that trust and enforcement will be essential for prediction markets seeking broader adoption.

He noted that stronger rulebooks, faster investigations, transparent disciplinary actions, and potential referrals to regulators such as the CFTC would help reinforce confidence in emerging betting and prediction platforms.

The comments echoed broader industry concerns that loosely governed markets could invite abuse during illiquid periods.

Debate Over Manipulation vs. Market Savvy

While some observers labeled the trade manipulative, others argued the strategy merely exploited publicly available market mechanics. The lack of explicit rules governing cross-market behavior between prediction platforms and spot exchanges leaves a gray area that regulators and platforms have yet to fully address.

As prediction markets continue to grow alongside crypto adoption, the line between aggressive trading and prohibited behavior remains blurred.

Implications for Prediction Markets

The Polymarket incident may serve as a stress test for the sector. It highlights how interconnected spot markets and prediction platforms have become and how quickly weaknesses can be exposed during periods of low liquidity.

Whether platforms respond with stricter rules, smarter automation, or enhanced surveillance could shape the future trajectory of crypto-based prediction markets.

Q&A

What is Polymarket?

Polymarket is a crypto-based prediction market where users trade contracts tied to the outcomes of real-world events, including asset price movements, politics, and macroeconomic developments.

Why did weekend liquidity matter in this case?

Weekend trading typically sees lower volumes, making prices more sensitive to large orders. This allowed the trader’s XRP purchase to influence settlement prices more easily.

Did the trader break any rules?

There is currently no public confirmation that platform rules were violated. However, the strategy has raised questions about market fairness and whether existing safeguards are sufficient.

Why are automated bots vulnerable?

Many bots rely on simple algorithms that react to price changes without accounting for context such as settlement timing, liquidity conditions, or adversarial strategies.

Could this lead to regulatory action?

Possibly. Increased scrutiny from regulators and calls for stronger oversight may follow as prediction markets grow and attract larger pools of capital.