Polymarket 2025 Six Major Profit Models Report, starting from 95 million on-chain transactions

Author: Lin Wanwan’s Cat

On the night of the 2024 US presidential election, a French trader netted $85 million on Polymarket.

This figure exceeds the annual performance of most hedge funds.

Polymarket, a decentralized prediction market handling over $9 billion in trading volume and gathering 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 exactly did the winners do right?

Recently, I wrote a series of strategies and systematically backtested 86 million on-chain trades, analyzing the position logic and entry/exit timing of top traders.

I summarized six proven profitable strategies: from information arbitrage based on French whale “neighbor resident adjustment” signals, to high-probability bond strategies with an annualized return of 1800%; from cross-platform price difference capture to 96% win-rate niche trading methods.

Our backtests reveal that top traders’ common traits are not “predictive ability,”

but three things:

Systematically capturing market mispricings, rigorous risk management bordering on obsession, and patiently building a crushing informational advantage 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 rather a systematic framework and replicable methodology for prediction market participants, especially beginners.

Keywords: prediction market; Polymarket; trading strategies; arbitrage; risk management; blockchain

I will present this in five parts. If you’re only interested in strategies, you can skip directly to Part 3.

1. Research Background

2. Evaluation Dimensions and Standards

3. Six Core Strategies of 2025

4. Position Management and Strategies

5. Conclusion

1. Research Background

In October 2025, ICE, the parent company of the NYSE, issued 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 election.

While mainstream polls all said “too close to call, impossible to predict,” 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 the line” truly force more honest judgments?

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

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

When media start checking odds first, investors begin referencing markets for decisions, and politicians monitor Polymarket instead of polls.

It is moving from gambling to a form of “pricing consensus.”

A market that makes Wall Street pay, regulators approve, and pollsters feel ashamed—worthy of serious study.

2. Research Methods and Evaluation Standards

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) Dune Analytics on-chain data dashboard;

(5) Chainalysis blockchain analysis reports.

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

2.2 Evaluation Dimensions and Weights

Strategy evaluation 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 that only 0.51% of wallets have over $1,000 in profit, and only 1.74% of whale accounts with over $50,000 in trading volume.

Risk-adjusted return (25% weight):

Calculates metrics like ROI and Sharpe ratio. Excellent traders typically maintain a 60-70% win rate and keep single-position risk exposure within 20-40% of total funds.

Strategy replicability (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 Criteria

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 power) manipulated a $7 million market settlement;

(2) Single trades with 40-50% or higher position sizes, akin to gambling;

(3) Strategies that cannot be verified or replicated (“black box” strategies);

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

3. 2025 Core Profit Strategies Review

1. Information Arbitrage: When a Frenchman understands elections better than all US pollsters

On the early morning of November 5, 2024, while CNN and Fox News hosts were cautiously saying “the race is tight,” an anonymous account Fredi9999’s position had already floated over $50 million in profit.

A few hours later, Trump announced 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.

While 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 neighbor 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 leaning toward Trump.” When he received 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 an $85 million return.

This might be the highest investment return in human history for market research. Currently, his total profit ranks first on Polymarket.

Replicability assessment: The threshold for information arbitrage is extremely high, requiring original research methodologies, large capital, and the psychological 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 “mind game,” cross-platform arbitrage is “a physical game”: dull, mechanical, but almost risk-free.

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

From April 2024 to April 2025, academic research recorded a figure: arbitrageurs extracted over $40 million in “riskless profit” from Polymarket. The top three wallets alone 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 same event’s NO price was $0.48.

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

But there’s a “fatal detail”: the two platforms may define the “same event” differently.

During the US government shutdown in 2024, a group of arbitrageurs found that Polymarket settled on “shutdown occurred” (YES), while Kalshi settled on “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 luck. Behind every cent of price difference are the details of settlement rules.

Replicability 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. There are even open-source arbitrage bot codes on GitHub. But as institutional capital flows in, the arbitrage window is shrinking visibly.

3. High-Probability Bond Strategy: Turning “almost certain” into an annualized 1800% 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” events.

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

For example: three days before the December 2025 Federal Reserve rate meeting, the “cut interest rate by 25 basis points” YES contract traded at $0.95. Economic data was clear, Fed officials’ speeches hinted no surprises. Buying at $0.95 and settling at $1 after three days yields 5.2%, paid out in 72 hours.

5% may seem small? Here’s a quick calculation: 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 nearly 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 surprises. A single mistake can wipe out dozens of successful trades’ profits. So top bond traders’ core skill isn’t finding opportunities but identifying “pseudo-certainties”: traps that look nailed but hide risks.

Replicability 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 capital reaches a certain size, the market simply doesn’t have enough 95%+ opportunities for you to “harvest.”

4. Liquidity Provision Strategy: Just earning “tolls”? 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 “run a casino” rather than “be a gambler”—they are liquidity providers (LPs).

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

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 gave an interview with Polymarket, sharing how he built an automated market-making system. At its peak, this system generated $700–$800 daily profit.

Starting with $10,000, he initially earned about $200 daily. As the system optimized and capital increased, earnings rose to $700–$800 daily. The core is leveraging Polymarket’s liquidity reward program: 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 metrics, estimates expected returns per $100 investment, and ranks strategies 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.

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

LP strategies are still feasible at the end of 2025, but returns decline and competition intensifies. The setup costs for high-frequency trading are higher than the wages of ordinary staff. High-end VPS infrastructure needs to be hosted near Polymarket servers. Quant algorithms are optimized for fast 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.

Replicability 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 reliant on unique insights as information arbitrage. It requires technical skills, but those can be learned.

5. Niche Specialization Strategy: The prediction market version of the 10,000-hour rule

Polymarket rankings show 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: total profit over $1.4 million, with a single biggest 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 changes during the game.

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

These cases share a common point: expert traders may only participate in 10-30 trades per year, but each with very 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 major tournament but then suffered significant losses in subsequent events.

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

Replicability assessment: This is the most time-intensive strategy but also the highest barrier. Once you establish an 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, Fed Chair Powell started speaking. Within 8 seconds after he said “we will adjust policy at the appropriate time,” the price of the “Fed cuts interest rate in December” contract on Polymarket jumped from $0.65 to $0.78.

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

Trader GCR said that 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 his speech today?” If you can know the answer 30 seconds earlier than others (by monitoring White House live streams instead of waiting for news), you can build a position before the price moves.

Some quantitative teams have industrialized this strategy. According to on-chain data analysis, between 2024 and 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 systems, preset decision scripts, and funds spread across multiple platforms.

But speed trading is becoming increasingly difficult. As more institutional capital enters, the arbitrage window shrinks from “minute-level” to “second-level,” making it nearly impossible for retail traders to participate. It’s a race with arms—retail tools are far inferior to institutional ones.

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

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;

Keep 20-40% of funds as reserves 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 appetite, suggested allocations are:

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

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

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

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

五、结论

2025 is a pivotal year for Polymarket’s transition from fringe experiment to mainstream finance.

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

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

New entrants should focus on: (1) Building informational advantages in a vertical niche; (2) Starting with small-scale bond strategies to gain 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 the “truth discovery mechanism through monetary voting.”

In this market, true edge does not come 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.