In-Depth Analysis of Polymarket Prediction Markets: Six Practical Strategies from French Traders Earning $85 Million in Information Arbitrage to High-Probability Bond Strategies with 1800% Annualized Returns, Revealing How Top Traders Maintain Profits in Zero-Sum Games. This article is adapted from a piece by Lin Wanwan’s Cat, compiled, translated, and written by PANews.
(Background: Leading Prediction Market Polymarket Announces Self-Built L2, Has Polygon Lost Its Ace?)
(Additional context: How to Achieve 40% Annualized Returns through Arbitrage on Polymarket?)

Table of Contents

• 1. Research Background
• 2. Methodology and Selection Criteria
  • 2.1 Data Sources
  • 2.2 Evaluation Dimensions and Weights
  • 2.3 Exclusion Standards
• 3. Review of Six Core Profit Strategies in 2025
  • 1. Information Arbitrage: When a French Whale Knows More Than US Polls
  • 2. Cross-Platform Arbitrage: The Art of “Picking Money” Between Markets
  • 3. High-Probability Bond Strategy: Turning “Almost Certain” into 1800% Annualized Business
  • 4. Liquidity Provision Strategy: Just Earning “Toll Fees”? Not That Simple
  • 5. Domain Specialization Strategy: The Prediction Market Version of the 10,000-Hour Rule
  • 6. Speed Trading Strategy: Front-Running Before the World Reacts
• 4. Risk Management and Strategy Portfolio
  • 4.1 Position Management Principles
  • 4.2 Strategy Portfolio Recommendations
• 5. Conclusion

On the night of the 2024 US Presidential Election, a French trader netted $85 million on Polymarket. This figure surpasses the annual performance of most hedge funds.

Polymarket, a decentralized prediction market with over $9 billion in trading volume and 314,000 active traders, is redefining the boundaries of “voting with money.”

But we must first be honest: prediction markets are a zero-sum game.

Only 0.51% of wallets achieved profits exceeding $1,000.

So, what did the winners do right?

Recently, I wrote a series of strategies and systematically backtested 86 million on-chain trades, dissecting the holdings logic and entry/exit timing of top traders, summarizing six proven profit strategies: from French whale’s “neighbor survey” information arbitrage to 1800% annualized high-probability bond strategies; from cross-platform price difference capture to 96% win rate domain specialization.

Backtracking reveals that top traders’ common traits are not “predictive ability,” but three things:

Systematically capturing market mispricings, rigorous risk management approaching obsession, and patience in establishing crushing informational advantages in a single domain.

If you’re reading this, I guess that by 2026, you will inevitably try it yourself sooner or later.

Of course, this is not a guide on “how to gamble,” but aims to provide prediction market participants, especially beginners, with a systematic strategic framework and replicable methodologies.

I will divide into five parts; if you’re only interested in strategies, you can skip directly to Part 3.

1. Research Background

2. Evaluation Dimensions and Criteria

3. Six Core Strategies of 2025

4. Position Management and Strategies

5. Conclusion

1. Research Background

In October 2025, NYSE parent ICE wrote a $2 billion check to Polymarket, valuing it at $9 billion.

One month later, Polymarket acquired a CFTC-licensed exchange, officially returning to the US. The “gray area project” expelled three years ago by regulation has now become a target pursued by traditional finance.

The turning point was the 2024 election.

While mainstream polls said “too close to call,” Polymarket’s odds consistently pointed to Trump. With $3.7 billion in bets, it predicted the outcome earlier and more accurately than professional polling agencies. Academia began re-examining an old question: does letting people “put money on their lips” truly force more honest judgments?

The internet’s first thirty years created three infrastructures: search engines tell you “what happened,” social media shows “what others think,” algorithm recommendations suggest “what you might want to see.” But one piece has always been missing: a place that reliably answers “what will happen next.”

Polymarket is filling this gap and becoming the first truly mainstream application in crypto, addressing the urgent need for “information pricing.”

When media start quoting odds in news, investors reference markets for decisions, politicians monitor Polymarket instead of polls.

It moves from betting to a form of “pricing consensus.”

A market that makes Wall Street pay, regulators approve, and polls pale in comparison deserves serious study.

2. Methodology and Selection Criteria

2.1 Data Sources

This research uses multiple data sources for cross-validation:

(1) Official Polymarket rankings data;

(2) Third-party analysis platform Polymarket Analytics (updated every 5 minutes);

(3) PolyTrack trader tracking tool;

(4) On-chain data dashboard Dune Analytics;

(5) Chainalysis blockchain analysis reports.

Data covers over 86 million trades and 17,218 market conditions from April 2024 to December 2025.

2.2 Evaluation Dimensions and Weights

Strategy selection adopts a multi-dimensional comprehensive assessment system, including:

Absolute profit ability (30% weight):

Centered on cumulative PnL, measuring total profit generated by the strategy. Data shows only 0.51% of wallets have over $1,000 PnL, and only 1.74% of whales with over $50,000 trading volume.

Risk-adjusted returns (25% weight):

Calculates ROI, Sharpe ratio, etc. Top traders maintain a 60-70% win rate, controlling single-position risk exposure within 20-40% of total capital.

Reproducibility (20% weight):

Assesses the systematic and rule-based nature of the strategy. Profits relying solely on insider info or luck are excluded.

Continuity and stability (15% weight):

Examines performance consistency across different market cycles, excluding “one-hit wonder” gambling-like gains.

Scalability (10% weight):

Analyzes the applicability of the strategy at larger capital scales, considering liquidity constraints and market impact costs.

2.3 Exclusion Standards

The following are not included in the best strategy selection:

(1) Suspected market manipulation, such as the UMA token governance attack in March 2025, where a whale holding 5 million UMA tokens (25% voting rights) manipulated a $7 million market settlement;

(2) Single trades with over 40-50% position size;

(3) Unverifiable or non-reproducible “black box” strategies;

(4) Insider trading relying on non-public information.

3. Review of Six Core Profit Strategies in 2025

1. Information Arbitrage: When a French Whale Knows More Than US Polls

On the early morning of November 5, 2024, while CNN and Fox News hosts cautiously discussed a “tight race,” an anonymous account Fredi9999 had already realized a profit exceeding $50 million.

A few hours later, Trump declared victory, and this account, along with 10 related wallets, ultimately harvested $85 million in profit.

The person behind the account is Théo, a French trader who previously worked on Wall Street.

When all mainstream polls showed Harris and Trump neck and neck,

he did something seemingly crazy: sold almost all liquid assets, raised $80 million, and bet everything on Trump winning.

Théo didn’t ask voters “who will you vote for,” but commissioned YouGov to conduct a special poll in Pennsylvania, Michigan, and Wisconsin, asking: “Who do you think your neighbors will vote for?”

The logic of this “neighbor effect” poll is simple: some people are ashamed to admit they support Trump, but they don’t mind saying their neighbors do.

The result was “shockingly pro-Trump.” Once he got the data, Théo increased his position from 30% to all-in.

This case reveals the essence of information arbitrage: it’s not about knowing more than others, but about asking the right questions. Théo spent less than $100,000 on polling, earning back $85 million.

This might be the highest investment return in human history. Currently, he ranks first in Polymarket’s earnings.

Reproducibility assessment: Information arbitrage requires a high threshold—original research methodology, large capital, and mental resilience to stick to judgments when “everyone says you’re wrong.” But its core idea—finding systematic biases in market pricing—is applicable to any controversial prediction market.

2. Cross-Platform Arbitrage: The Art of “Picking Money” Between Markets

If information arbitrage is a “mental game,” cross-platform arbitrage is a “physical activity”: dull, mechanical, but almost risk-free.

Its principle is simple: the same event, store A sells for $45, store B for $48, buy one at each, hedge, and profit from the spread regardless of the outcome.

From April 2024 to April 2025, academic research recorded a total of over $40 million in “riskless profit” extracted from Polymarket, with the top three wallets earning $4.2 million.

A real example: on a certain day in 2025, the question “Bitcoin surpasses $95,000 in one hour” had a YES price of $0.45 on Polymarket, while on competitor Kalshi, the NO price was $0.48.

Smart traders buy both sides, with a total cost of $0.93. Whether Bitcoin rises or not, they can cash out at $1, earning 7.5% riskless profit within an hour.

But there’s a “fatal detail”: the definition of the “same event” may differ across platforms.

During the US government shutdown in 2024, arbitrageurs found that Polymarket settled “shutdown occurred” (YES), while Kalshi settled “shutdown did not occur” (NO).

They thought they had a riskless hedge, but both sides lost money.

Why? Polymarket’s settlement standard is “OPM publishes shutdown announcement,” while Kalshi requires “actual shutdown lasting over 24 hours.”

Arbitrage isn’t blind betting. Every cent of spread behind it is a detail in the settlement rules.

Reproducibility assessment: This is the lowest threshold among the six strategies. You only need to open accounts on multiple platforms, some initial capital, and patience to compare prices. There are even open-source arbitrage bots on GitHub. But as institutional capital flows in, arbitrage windows are narrowing visibly.

3. High-Probability Bond Strategy: Turning “Almost Certain” into 1800% Annualized Business

Most people come to Polymarket for excitement: betting on dark horses, predicting upsets.

But the “smart money” does the opposite: they buy those “already nailed down” events.

Data shows that over $10,000 orders on Polymarket occur at prices above $0.95, with 90% happening at such levels. What are these whales doing? They are “bonding,” buying almost certain events like bonds.

For example: three days before the December 2025 Federal Reserve rate meeting, the YES contract for a “25 basis point rate cut” trades at $0.95. Economic data is clear, Fed officials’ speeches are explicit, no surprises expected. Buy at $0.95, settle in three days for $1, earning 5.2% in 72 hours.

5% may seem small? Let’s do the math: if you find two such opportunities weekly, that’s 52 weeks × 2 × 5% = 520% simple annual return. With compounding, easily over 1800% annualized. And the risk is near zero.

Some traders rely on this strategy, doing only a few trades weekly, earning over $150,000 annually.

Of course, “almost certain” does not mean “absolutely certain.”

The biggest enemy of bond strategies is black swans—those 0.01% probability events. One mistake can wipe out dozens of successful profits. So top bond traders’ core skill isn’t finding opportunities but identifying “pseudo-certainty”: traps that look nailed but hide risks.

Reproducibility assessment: This is the easiest strategy for beginners. No deep research needed, no speed advantage required—only patience and discipline. But its profit ceiling is also the lowest. Once your capital reaches a certain size, the market simply doesn’t have enough 95%+ opportunities for you to “harvest.”

4. Liquidity Provision Strategy: Just Earning “Toll Fees”? Not That Simple

Why do casinos always make money? Because they don’t gamble with you; they just take a cut.

On Polymarket, some choose to “act as a casino” rather than “be a gambler”—they are liquidity providers (LP).

LPs’ job: place both buy and sell orders on the order book, earning the spread. For example, place a buy at $0.49 and a sell at $0.51; regardless of who trades, you earn the $0.02 difference. You don’t care about the event outcome, only whether someone trades.

Polymarket launches new markets daily. New markets are characterized by low liquidity, large spreads, and many retail traders. For LPs, this is paradise. Data shows that providing liquidity in new markets can yield an annualized equivalent return of 80%-200%.

A trader named @defiance_cr shared in an interview how he built an automated market-making system. At its peak, it generated $700–$800 daily profit.

Starting with $10,000, initially earning about $200 daily, optimized the system and scaled up funds, earning $700–$800 daily. The core is leveraging Polymarket’s liquidity rewards: placing orders on both sides of the market can earn nearly triple rewards.

His system has two core modules: a data collection module that pulls historical prices via Polymarket API, calculates volatility indicators, estimates expected returns per $100 investment, and ranks by risk-adjusted returns; and a trading execution module that automatically places orders based on preset parameters—narrow spreads in liquid markets, wider spreads in volatile markets.

But after the election, Polymarket’s liquidity rewards dropped sharply.

LP strategies remain feasible at the end of 2025, but returns decline and competition intensifies. High-frequency trading setup costs exceed typical employee salaries. High-end VPS infrastructure must be hosted near Polymarket servers. Quant algorithms are optimized for rapid execution.

So don’t envy “those traders earning $200,000 a month—they are the top 0.5%.”

This “market-making + prediction” combo is standard for high-level players.

Reproducibility assessment: LP strategies require deep understanding of market microstructure, including order book dynamics, spread management, inventory risk control. It’s not as mechanical as arbitrage nor as reliant on unique insights as information arbitrage; it lies in between, requiring skills that can be learned.

5. Domain Specialization Strategy: The Prediction Market Version of the 10,000-Hour Rule

On Polymarket’s leaderboard, an interesting phenomenon: the most profitable traders are almost all “specialists.” They are not generalists with a little knowledge of everything, but experts with crushing advantages in narrow domains.

Some real cases:

Sports market giant HyperLiquid0xb: over $1.4 million in total profit, with a single largest gain of $755,000 from a baseball game prediction. He is as familiar with MLB data as a professional analyst, able to adjust judgments quickly based on pitcher rotations and weather during the game.

Market maven Axios: maintains a 96% success rate in markets like “Will Trump say ‘cryptocurrency’ during speech.” His method is simple but extremely time-consuming: analyzing all past public statements of the target, counting the frequency and context of specific words, building a predictive model. While others are still “betting,” he is already “calculating.”

These cases share a common point: expert traders may only participate in 10-30 trades per year, but each with extremely high confidence and profit potential.

So specialization is more profitable than breadth.

Of course, Wanwan also saw a sports expert, SeriouslySirius, who lost $440,000 in a single world cup bet, then suffered significant losses in subsequent events.

If you only “know a little,” you’re just giving money to the experts. Of course, “knowing” is also another form of gambling.

Reproducibility assessment: This is the most time-intensive strategy but also the highest barrier. Once you establish informational advantage in a domain, it’s very hard to replicate. It’s recommended to choose fields where you already have knowledge or professional background.

6. Speed Trading Strategy: Front-Running Before the World Reacts

On a Wednesday afternoon in 2024, at 2 pm, Fed Chair Powell begins speaking. Within 8 seconds after he says “we will adjust policy at the appropriate time,” the “Fed cuts interest rate in December” contract on Polymarket jumps from $0.65 to $0.78.

What happened in those 8 seconds? A small group of “speed traders” monitored live streams, triggered preset conditions, and placed orders before the average person even understood what Powell said.

Trader GCR said, the core of speed trading is “reaction.” It exploits the time window between information generation and market digestion, usually just a few seconds to minutes.

This strategy is especially effective in “Mention markets.” For example, “Will Biden mention China in today’s speech?” If you can know the answer 30 seconds faster than others (by monitoring White House live streams instead of waiting for news), you can position before the price moves.

Some quantitative teams have industrialized this approach. According to on-chain data, between 2024-2025, top algorithmic traders executed over 10,200 speed trades, earning a total of $4.2 million. Their tools include low-latency APIs, real-time news monitoring, preset decision scripts, and capital spread across multiple platforms.

But speed trading is becoming increasingly difficult. As more institutional capital enters, arbitrage windows shrink from “minute-level” to “second-level,” making it nearly impossible for retail traders to participate. It’s a race of armament, and retail tools are far inferior to institutions.

Reproducibility assessment: Unless you have technical expertise and are willing to invest time developing trading systems, it’s not recommended. The alpha from speed trading is rapidly disappearing, leaving less room for retail. If you want to participate, start with low-competition niche markets (local elections, niche sports).

4. Risk Management and Strategy Portfolio

4.1 Position Management Principles

Successful traders generally follow these position management principles:

Hold 5-12 uncorrelated positions simultaneously; mix short-term (days) and long-term (weeks/months) holdings;

Reserve 20-40% of capital for new opportunities;

Limit risk per trade to no more than 5-10% of total capital.

Over-diversification (30+ positions) dilutes returns, while over-concentration (1-2 positions) increases risk.

Optimal number of positions is usually between 6-10.

4.2 Strategy Portfolio Recommendations

Based on risk preferences, suggested allocations are:

Conservative investors: 70% bonds + 20% liquidity provision + 10% copy trading.

Balanced investors: 40% domain specialization + 30% arbitrage + 20% bonds + 10% event-driven.

Aggressive investors: 50% information arbitrage + 30% domain specialization + 20% speed trading.

Regardless of the mix, avoid betting more than 40% of capital on a single event or highly correlated events.

5. Conclusion

2025 is a critical year for Polymarket’s transition from experimental edge to mainstream finance.

The six profit strategies reviewed—information arbitrage, cross-platform arbitrage, high-probability bonds, liquidity provision, domain specialization, and speed trading—represent verified sources of alpha in prediction markets.

In 2026, prediction markets will face fiercer competition and higher barriers to professionalism.

New entrants are advised to focus on: (1) Building informational advantages in a vertical niche; (2) Starting small with bond strategies to accumulate experience; (3) Using tools like PolyTrack to track top traders’ patterns; (4) Staying closely updated on regulatory changes and platform rule updates.

The essence of prediction markets is “a truth discovery mechanism through money voting.”

In this market, true advantage comes not from luck, but from better information, rigorous analysis, and disciplined risk management. May this review serve as a systematic map for you in this new world.