01 — Getting Started
Overview

What PredictedPoly is, who it's for, and how it fits into your Polymarket workflow.

Info
PredictedPoly is an AI analysis layer on top of Polymarket data. We do not facilitate trades — all betting happens directly on Polymarket.

What is PredictedPoly?

Polymarket is one of the largest prediction markets in the world — billions of dollars in volume flow through markets on politics, crypto, geopolitics, and culture. The crowd often prices these markets efficiently. But not always.

PredictedPoly is an AI that finds when the crowd is wrong. By combining historical market data, live news sentiment, whale wallet tracking, and base-rate calibration, we generate independent probability estimates for the most popular Polymarket bets — then surface the gaps.

Who is this for?

UserUse Case
Active tradersIdentify markets where crowd pricing diverges significantly from AI-implied probability
Casual bettorsQuickly understand which side of a market has an informational edge, without deep research
ResearchersStudy systematic biases in prediction market crowds across categories and time windows
News followersUnderstand the probability-weighted view on current events, grounded in market data
02 — Getting Started
Quick Start

How to read a PredictedPoly prediction card in under 2 minutes.

01

Find a market you're interested in

Browse prediction cards on the main page. Filter by category: Crypto, Politics, Geopolitics, or Culture.

02

Compare Market vs AI probabilities

Each card shows two bar sets — Polymarket odds (what the crowd thinks) and AI Predicted (what our model computes). The gap is the signal.

03

Check the Edge badge

The card footer shows the AI verdict: Undervalued Pick means the market is underpricing this outcome. Market Overpriced means the favorite is getting too much love.

04

Read the AI Reasoning

Click AI Reasoning ▾ to expand the model's logic. Each bullet is a specific signal contributing to the AI's estimate.

05

Trade on Polymarket

We don't execute trades. Click through to Polymarket to act on the analysis. Always size positions according to your own risk tolerance.

Note
An AI edge of 8%+ is our threshold for flagging a market. Smaller divergences are within noise range and are not highlighted.
03 — Getting Started
How It Works

The full pipeline — from raw Polymarket data to a published prediction with an edge score.

// PredictedPoly AI Pipeline

1. DATA INGESTION
   Polymarket API → live odds, volume, order book depth
   Refresh: every 15 minutes across all active markets

2. SIGNAL EXTRACTION
   → Historical resolution patterns (50,000+ outcomes)
   → News sentiment velocity (7-day rolling window)
   → Whale wallet positioning delta
   → Volume anomaly detection

3. BASE RATE CALIBRATION
   Historical accuracy = f(category, time_horizon, vol)
   Crowd bias correction applied per market type

4. PROBABILITY GENERATION
   AI_probability = weighted_ensemble(signals)

5. EDGE DETECTION
   edge = AI_probability - market_probability
   if |edge| >= 0.08 → flag as opportunity

6. PUBLISH
   Top-volume markets updated every 15 min

Update Frequency

Market TypeRefreshReason
Crypto price markets15 minHigh volatility, fast-moving signals
Geopolitical events1 hourBreaking news can rapidly shift probabilities
Politics / elections6 hoursSlower-moving, poll and news cycle driven
Culture / entertainmentDailyLow-frequency sentiment signals sufficient
04 — AI Model
Methodology

The math, the biases we correct for, and how we validate the model.

Systematic Biases We Correct For

BiasDescriptionCorrection
Favorite-longshot biasCrowds overbet favorites, underprice longshotsRegression toward base rate for extreme odds
Recency biasLate-breaking news moves markets disproportionatelyNews velocity discount on last-24h signals
Narrative overconfidenceStrong public narratives create sustained mispricingsNarrative sentiment scored and faded with base rate
Late momentum underpricingMarkets slow to update on genuine momentum shiftsTrailing 7-day momentum signal weighted up

Probability Formula

P_ai = α · P_market + β · P_historical + γ · S_sentiment + δ · S_whale + ε · S_volume

Where: α + β + γ + δ + ε = 1.0
Weights are market-category specific — see Data Signals

Validation

We backtest against 50,000+ resolved Polymarket outcomes, evaluated on:

  • Calibration — when we say 70%, it should resolve YES ~70% of the time
  • Edge accuracy — flagged picks should outperform market odds in aggregate
  • Brier Score — overall probabilistic accuracy vs. raw market odds
Tip
Our model's Brier Score improvement over raw Polymarket odds is approximately +0.018 on the validation set — meaningful but modest. Prediction markets are hard to beat systematically.
05 — AI Model
Data Signals

The 7 input streams feeding the AI model, with weights that vary by market category.

#SignalSourceWeight Range
S1Historical Resolution Patterns50,000+ resolved outcomes20–40%
S2News Sentiment Velocity3,000+ news sources, 7-day rolling15–35%
S3Whale Wallet PositioningOn-chain analysis of large positions10–25%
S4Social Sentiment ScoreTwitter/X, Reddit, Telegram5–20%
S5Volume Anomaly DetectionLive order book + volume delta10–20%
S6Expert ConsensusAnalyst reports, institutional signals5–15%
S7Base Rate CalibrationHistorical frequency of similar events10–20%

Weights by Category

CRYPTO       S2: 30% · S3: 25% · S5: 20% · S1: 20% · S4: 5%
POLITICS     S1: 35% · S6: 25% · S7: 20% · S2: 10% · S4: 10%
GEOPOLITICS  S2: 35% · S6: 25% · S1: 20% · S7: 15% · S4: 5%
CULTURE      S4: 30% · S2: 30% · S1: 25% · S6: 15%
06 — AI Model
Confidence Score

Every prediction has a 0–100 confidence score reflecting signal agreement, not outcome probability.

Confidence = f(signal_agreement, data_freshness, market_liquidity, historical_accuracy)

Range: 0–100 · Minimum to publish: 45
ScoreLabelInterpretation
0–44LowSignals conflicted. Not published.
45–59MediumModerate agreement. Wide error bars. Informational only.
60–74Medium-HighGood convergence. Worth considering in decisions.
75–89HighStrong agreement. Highest-conviction predictions.
90–100Very HighNear-unanimous. Rare — high-liquidity markets only.
Note
A high confidence score does not mean the AI is right. It means signals agree. Black swan events and model blind spots can still cause high-confidence predictions to fail.
07 — AI Model
Edge Detection

How PredictedPoly identifies mispricings — and what to do with them.

edge(outcome) = P_ai(outcome) − P_market(outcome)

edge > +0.08 → Undervalued (AI thinks YES is cheap)
edge < −0.08 → Overpriced (AI thinks YES is expensive)
|edge| < 0.08 → No flag (within noise range)
BadgeMeaningExample
🎯 UndervaluedMarket underpricing. AI sees higher probability.Sinners 18% market / 34% AI = +16pp
⚠️ OverpricedMarket overpricing the favorite.BTC $100k YES 51% / 44% AI = −7pp
✅ AlignedAI and market agree. Direction confirmed.BTC $70k — both bullish
📊 Broadly AlignedSmall divergence. Near-identical direction.Newsom 25% / 22% AI
Risk
Edge scores are statistical signals, not guaranteed winners. Edges are only meaningful in aggregate across many markets. Position-sizing matters more than any single prediction.
08 — Markets
Market Categories

Four primary categories, each with a tailored AI model configuration.

Crypto

Price targets, ETF approvals, protocol launches. Fast-moving — whale wallets and volume anomalies dominate the signal mix.

Examples: Bitcoin $100k EOY, ETH ETF approval, BTC price by end of month.

Politics

Elections, nominations, policy decisions. Deep historical data, driven by polling and structural indicators. Base rates matter most.

Examples: 2028 Democratic nominee, Senate majority control, Trump approval rating.

Geopolitics

Conflict escalation, ceasefires, regime changes. Hardest to price — information moves fast, markets are often slow to update.

Examples: US-Iran ceasefire, Iranian regime fall, NATO Article 5 invocation.

Culture

Awards, box office, sports outcomes. Social sentiment and media coverage velocity are key. These markets over-rely on public narrative.

Examples: Oscar Best Picture, Super Bowl winner, album chart position.

09 — Markets
Reading Predictions

A full anatomy of a PredictedPoly prediction card.

┌─────────────────────────────────────────────┐
│ [Category]                      [Volume]    │
├─────────────────────────────────────────────┤
│ Market Title / Question                      │
├─────────────────────────────────────────────┤
│ — POLYMARKET ODDS                            │
│ Outcome A  ████████████░░░░  79%            │
│ Outcome B  ████░░░░░░░░░░░░  18%            │
│                                              │
│ — AI PREDICTED                               │
│ Outcome A  █████████░░░░░░░  61%  ← lower   │
│ Outcome B  ███████░░░░░░░░░  34%  ← higher  │
├─────────────────────────────────────────────┤
│ [AI Reasoning ▾]                             │
├─────────────────────────────────────────────┤
│ 🎯 Undervalued Pick      Outcome B +16pp    │
└─────────────────────────────────────────────┘
ElementWhat it tells you
Bar gap sizeBigger gap = larger AI edge. Tiny gap = aligned.
Edge pp"+16pp" means AI assigns 16 percentage points more probability than the market
VolumeHigher volume = more efficient market. Low-volume can have larger mispricings.
AI Reasoning bulletsEach bullet is an independent signal. More bullets = more sources agreeing.
10 — Markets
Update Schedule

When and how predictions are refreshed — scheduled cadence plus event-driven triggers.

TriggerMarkets AffectedLatency
Major news eventAll relevant markets< 10 minutes
Whale position change ≥5%Crypto, high-volume< 15 minutes
Market odds shift ≥3ppAll markets< 15 minutes
Scheduled (crypto)All crypto marketsEvery 15 min
Scheduled (geo/politics)All non-cryptoEvery 1–6 hours
11 — Reference
Glossary

Key terms used throughout PredictedPoly.

TermDefinition
P_marketCurrent Polymarket probability — the price of a YES share
P_aiPredictedPoly's AI-computed probability for the same outcome
EdgeP_ai minus P_market. Positive = underpriced. Negative = overpriced.
Confidence Score0–100 score reflecting signal agreement, not outcome probability
WhaleA participant holding a large position (>$10k) whose moves carry informational weight
Brier ScoreScoring rule for probability accuracy. Lower is better. Ranges 0–2.
Base RateHistorical frequency of similar events resolving YES, used as a prior
Volume AnomalyUnusual spike or drop in volume that may signal informed trading
Favorite-Longshot BiasTendency to underprice longshots and overprice heavy favorites
CLOBCentral Limit Order Book — Polymarket's trading mechanism
12 — Reference
FAQ

Common questions about PredictedPoly.

Is this financial advice?

No. PredictedPoly is an informational tool. Nothing on this site constitutes financial, investment, or betting advice.

How accurate is the AI?

On backtested data, our model improves over raw Polymarket odds by approximately +0.018 Brier Score. Polymarket is one of the most efficient prediction markets in the world. Expect to be wrong often even when the edge is real.

Why are some markets not covered?

We prioritize markets by volume and data availability. Currently we cover approximately the top 50 markets by volume.

Can I get probabilities via API?

Not yet. A public API is on the roadmap for Q3 2026. Follow @PredictedPoly for updates.

How do I report a wrong prediction?

DM @PredictedPoly on X/Twitter after the market resolves.

13 — Reference
Disclaimer

Please read before using PredictedPoly predictions in any financial decisions.

Legal
PredictedPoly is not a financial advisor, broker, or licensed investment service. All content is for informational and entertainment purposes only.

No Financial Advice

Nothing on predictedpoly.one constitutes financial advice, investment advice, trading advice, or any other sort of advice.

AI Limitations

Our AI model has known limitations: data lag, model bias, inability to process private information, sensitivity to outlier events, and systematic blind spots. Predictions can and will be wrong.

No Affiliation with Polymarket

PredictedPoly is an independent analysis service, not affiliated with or endorsed by Polymarket. We use Polymarket's public market data to generate analysis.

Betting Risk

Prediction market trading involves financial risk. You may lose money. Never bet more than you can afford to lose.

Regulatory Notice

Prediction market betting may not be legal in your jurisdiction. It is your responsibility to ensure compliance with local laws.