In-Depth Analysis of Polymarket Prediction Markets: Six Practical Strategies from French Trader’s $85 Million Arbitrage to 1800% Annualized High-Probability Bond Strategy, Revealing How Top Traders Continually Profit 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 Strategy: When a French Whale Knows More About the Election Than US Polls
  • 2. Cross-Platform Arbitrage: The Art of “Picking Money” Between Two Markets
  • 3. High-Probability Bond Strategy: Turning “Almost Certain” into an 1800% Annual Business
  • 4. Liquidity Provision Strategy: Earning “Toll Fees”? Not That Simple
  • 5. Domain Expertise 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 Election Night 2024 in the US, a French trader netted $85 million on Polymarket. This figure surpasses most hedge funds’ annual performance.

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 over $1,000 in profit.

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 spread capturing to 96% win rate domain expertise tactics.

Backtracking reveals that top traders’ common traits are not “predictive ability,”

but three things:

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

If you’re reading this, I guess 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 methodology.

I will divide it 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 in 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 by regulation three years ago has now become a target sought after by traditional finance.

The turning point was the 2024 US 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 firms. Academia began re-examining an old question: does letting people “put money on the line” 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,” algorithmic 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 checking odds before writing news, investors begin referencing markets for decisions, and 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 leaderboard 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 (weight 30%):

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

Risk-adjusted return (weight 25%):

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 (weight 20%):

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

Continuity and stability (weight 15%):

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

Scalability (weight 10%):

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 the market settlement worth $7 million;

(2) Single trades with over 40-50% position size, akin to gambling;

(3) Strategies that are unverified or non-reproducible “black box” models;

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

3. Review of Six Core Profit Strategies in 2025

1. Information Arbitrage Strategy: When a French Whale Knows More About the Election 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 over $50 million in unrealized gains.

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

The account owner 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 did 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 profit leaderboard.

Reproducibility assessment: Information arbitrage requires a high threshold—original research methodology, large principal, 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 Two Markets

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

The 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. The top three wallets earned $4.2 million.

A real case: 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 bought both sides, with a total cost of $0.93. Whether Bitcoin rises or falls, 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 releases 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, have some initial capital, and patience to compare prices. Open-source arbitrage bots are available on GitHub. But as institutional capital flows in, arbitrage windows are shrinking visibly.

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

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

For example: three days before the December 2025 Fed rate meeting, the “cut 25 basis points” YES contract 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%, with 72 hours to profit.

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—0.01% chance 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 most beginner-friendly strategy. No deep research needed, no speed advantage required—only patience and discipline. But its profit ceiling is also the lowest. Once your principal reaches a certain size, the market won’t have enough 95%+ opportunities for you to “harvest.”

4. Liquidity Provision Strategy: 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 “be the casino” rather than “be the gambler”—they are liquidity providers (LPs).

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, he initially earned about $200 daily. With system optimization and capital expansion, earnings increased to $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 includes 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 yield; and a trading execution module that automatically places orders based on preset parameters—narrow spreads in liquid markets, wider spreads in volatile ones.

However, after the US election, Polymarket’s liquidity rewards significantly declined.

LP strategies remain feasible at the end of 2025, but returns decrease 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, etc. It’s not as mechanical as arbitrage nor as insight-dependent as information arbitrage. It lies between, requiring skills that can be learned.

5. Domain Expertise 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 superficial knowledge but experts with crushing advantages in narrow domains.

Some real examples:

Sports market giant HyperLiquid0xb: total profit over $1.4 million, with a single best bet of $755,000 on a baseball game prediction. His familiarity with MLB data rivals professional analysts, allowing quick adjustments based on pitcher rotations and weather during the game.

Market maverick Axios: maintains a 96% success rate in markets like “Will Trump say ‘cryptocurrency’ during his speech?” His method is simple but 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 trait: 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 championship 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 a 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 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 build positions 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 distributed 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 lag far behind 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 unrelated 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.

The 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 expertise + 30% arbitrage + 20% bonds + 10% event-driven.

Aggressive investors: 50% information arbitrage + 30% domain expertise + 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 pivotal 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 expertise, and speed trading—represent verified sources of alpha in prediction markets.

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

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) Tracking top traders using tools like PolyTrack; (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.