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Prediction Market Methodology: How PredictionHero Aggregates and Standardizes Real-Time Data

How PredictionHero Aggregates and Standardizes Real-Time Prediction Market DataPredictionHero is a prediction market aggregator and intelligence platform designed to make real-time prediction market data easier to compare, analyze, and understand across platforms.This methodology document explains how PredictionHero collects, standardizes, ranks, and interprets prediction market probabilities, prediction market odds, and related market data across platforms including Polymarket, Kalshi, Opinion, Limitless, and Predict.More platforms will be added in the future, which will be further reflected below.It covers:
  • probability calculations
  • prediction market consensus methodology
  • market matching systems
  • Resolution Divergence Alerts (RDA)
  • trending and breaking market logic
  • filtering systems
  • data freshness standards
  • platform-specific limitations
PredictionHero does not create markets, execute trades, or determine outcomes. The platform aggregates and standardizes publicly available prediction market data from external venues to improve cross-platform comparability and market intelligence.

What PredictionHero Does

Prediction markets are fragmented across multiple platforms, each with different rules, liquidity profiles, user bases, and market structures.PredictionHero aggregates these markets into a unified interface that allows users to:
  • compare prediction market odds across platforms
  • analyze real-time prediction market data
  • monitor market sentiment
  • identify probability divergence
  • discover trending prediction markets
  • evaluate resolution rule differences
  • filter and rank markets across categories and venues
Instead of manually comparing platforms like Polymarket vs Kalshi, users can analyze cross-platform prediction market data from a single interface.PredictionHero is designed for:
  • traders
  • analysts
  • journalists
  • researchers
  • and general users seeking structured prediction market intelligence

Data Sources & Platform Coverage

PredictionHero aggregates data from multiple prediction market platforms and event exchanges.Current supported platforms include:

Polymarket

A crypto-native prediction market platform known for high-volume political, geopolitical, sports, and cryptocurrency markets.

Kalshi

A US-regulated event exchange focused on economics, politics, weather, and current event forecasting markets.

Opinion

A prediction market platform focused on event-driven forecasting and real-time public sentiment markets.

Limitless

A blockchain-based prediction market platform supporting a broad range of speculative and event-driven markets.

Predict

A prediction market platform focused on crowd-sourced forecasting and speculative event markets.

From these platforms, PredictionHero collects

  • Yes/No prices
  • implied probabilities
  • bid and ask prices
  • trading volume
  • liquidity metrics
  • market status (active, resolved, disputed)
  • resolution criteria
  • event metadata
  • category classifications

Important Note

PredictionHero does not estimate, simulate, or invent probabilities.All probabilities, pricing, and market activity displayed on the platform originate from external prediction market platforms and their users.

How Prediction Market Probabilities Are Calculated

Prediction markets express probability through price.A “Yes” price of $0.70 corresponds to a 70% implied probability.A “Yes” price of $0.25 corresponds to a 25% implied probability.PredictionHero standardizes these implied probabilities across platforms to improve comparability between markets that may otherwise use different formatting or market structures.

Example

  • Yes Price: $0.72
  • Implied Probability: 72%
PredictionHero does not modify or reinterpret the underlying probabilities generated by source platforms.

Prediction Market Consensus Methodology

When multiple markets reference the same real-world event, PredictionHero may calculate a cross-platform prediction market consensus.By default, consensus is calculated using a simple average of implied probabilities across grouped markets.

Example

  • Platform A: 60%
  • Platform B: 64%
  • → Consensus Probability: 62%

Why Consensus Matters

Different prediction market platforms often contain:
  • different participants
  • different liquidity profiles
  • different market incentives
  • different information flows
Comparing Polymarket vs Kalshi probabilities, for example, can reveal differences in sentiment, pricing efficiency, or event interpretation.Consensus provides a broader view of prediction market sentiment across platforms rather than relying on a single venue.

Resolution Divergence Alerts (RDA)

Why Resolution Rules Matter

Markets that appear identical can still resolve differently across platforms.PredictionHero identifies these inconsistencies using Resolution Divergence Alerts (RDA).RDA is designed to detect situations where multiple prediction markets reference the same event but contain materially different resolution criteria.

What RDA Analyzes

PredictionHero compares:
  • resolution triggers
  • timing conditions
  • source data requirements
  • official rule wording
  • dispute handling
  • edge case definitions

Example

Two markets may ask: “Will Candidate X win the election?”However:
  • Platform A resolves using official government certification
  • Platform B resolves using major media projections
Same headline question. Different resolution logic.

Why This Matters

If users are unaware of these differences, they may incorrectly assume two markets carry identical risk profiles.In reality, they may be exposed to:
  • resolution ambiguity
  • timing discrepancies
  • interpretation risk
  • settlement divergence
PredictionHero surfaces these risks before market resolution whenever possible.

How Markets Are Matched & Grouped

Not all similar-looking prediction markets represent the same event.PredictionHero uses a combination of:
  • semantic title analysis
  • outcome structure comparison
  • entity recognition
  • time alignment
  • market classification logic
to determine whether markets should be:
  • grouped together
  • displayed as related
  • or treated as separate events

Example

  • “Will Bitcoin hit $100K in 2026?”
  • vs
  • “Will BTC exceed $100K before Jan. 1?”
These markets may appear similar but contain different timing structures and resolution conditions.PredictionHero attempts to preserve these distinctions while still enabling meaningful comparison across platforms.

Market Filters & Search Methodology

PredictionHero includes a multi-dimensional prediction market filtering and ranking system designed to improve market discovery, comparability, and analysis.Markets can be filtered based on:
  • probability
  • volume
  • liquidity
  • spread
  • timing
  • platform
  • category
  • activity
  • market structure
  • and resolution status
By default, markets are ranked by volume unless otherwise specified.Some filters are informational. Others are designed to surface unusual market behavior, pricing inefficiencies, or elevated market activity.

Probability Filter ("Strike Zone")

The Probability Filter allows users to identify markets within a selected implied probability range.Example Uses
  • underdog markets below 20%
  • near-certain outcomes above 90%
  • “coin flip” markets between 45–55%
Probabilities are standardized across supported prediction market platforms whenever possible.

Volume Filters

PredictionHero supports multiple volume-based filters designed to identify where prediction market activity is concentrated.Total VolumeFilters markets using cumulative lifetime trading volume.Useful for
  • identifying major prediction markets
  • filtering out low-signal contracts
  • monitoring large-scale market participation
24-Hour VolumeFilters markets based on recent trading activity.Useful for
  • identifying breaking developments
  • monitoring short-term momentum
  • detecting sudden attention shifts

Liquidity Filter

The Liquidity Filter identifies markets with sufficient market depth and tradability.Higher liquidity generally corresponds to:
  • tighter spreads
  • lower slippage
  • more reliable price discovery
Lower-liquidity markets may experience:
  • wider spreads
  • temporary inefficiencies
  • elevated volatility

Spread Filter

The Spread Filter screens prediction markets based on bid-ask spread size.Spread is calculated as: Spread = Ask Price − Bid PriceWhy Spread MattersSmaller spreads generally indicate:
  • healthier market conditions
  • stronger liquidity
  • more efficient pricing
Wider spreads may indicate:
  • uncertainty
  • lower liquidity
  • elevated pricing inefficiency
Users may filter by predefined spread thresholds or custom spread ranges.

Platform Filter

The Platform Filter allows users to isolate prediction markets from specific venues.Supported platforms may include:
  • Polymarket
  • Kalshi
  • Opinion
  • Limitless
  • Predict
This is useful for:
  • comparing Polymarket vs Kalshi pricing
  • analyzing venue-specific sentiment
  • identifying structural market differences
  • monitoring platform-specific activity

Event Timing Filters

PredictionHero supports multiple time-based filtering systems.Ends InFilters markets based on expected resolution timeframe.Examples include
  • ending today
  • ending this week
  • long-duration contracts
Ending SoonHighlights markets approaching resolution.These markets may experience:
  • elevated volatility
  • rapid probability movement
  • increased trading activity
New MarketsSurfaces recently launched prediction markets entering early price discovery.New markets may:
  • react rapidly to breaking narratives
  • contain temporary inefficiencies
  • initially display lower liquidity

Category Filters

PredictionHero classifies markets into categories including:
  • Politics
  • Elections
  • Crypto
  • Sports
  • Financials
  • Economics
  • Science & Technology
  • Entertainment
  • Companies
  • Geopolitics
  • Other emerging sectors
This classification system is designed to improve thematic analysis and large-scale market discovery.

Market Structure Filters

PredictionHero supports filtering based on contract and market structure.Examples include:
  • binary markets
  • multi-outcome markets
  • range-based contracts
  • active vs resolved markets
  • disputed markets
This helps users compare structurally similar prediction markets more accurately.

Activity & Momentum Filters

Certain filters are designed to surface unusual prediction market behavior.Signals may include:
  • rapid price movement
  • abnormal volume acceleration
  • elevated short-term activity
  • sudden liquidity inflows
These systems are intended to identify markets experiencing meaningful shifts in sentiment or participation.

Exclusion Filters

Users may exclude:
  • inactive markets
  • resolved markets
  • low-liquidity contracts
  • low-signal categories
  • structurally irrelevant markets
This improves discovery quality and reduces noise across large market datasets.

Saved Filters & Custom Screening

PredictionHero allows users to save custom filter combinations for recurring workflows and market monitoring.Example Use Cases
  • high-liquidity political markets ending this week
  • crypto markets with elevated volatility
  • low-spread markets above a volume threshold
This transforms PredictionHero from a simple prediction market aggregator into a customizable market intelligence and discovery platform.
PredictionHero’s Trending system is designed to identify markets experiencing meaningful increases in activity, participation, or attention."Trending" isn't based on vibes. It's based on data.Every 15 minutes, PredictionHero computes a trending_score for every eligible market using a five-signal composite formula:The five signals and their weights
  • Volume velocity — how fast trading volume is accelerating relative to the market's own 7-day rolling average, capped at 10× to prevent outlier distortion
  • Price movement — magnitude and direction of recent price shifts, a direct proxy for changing beliefs
  • Capital commitment — new money entering the market; measured as change in open interest on Kalshi, change in liquidity on Polymarket
  • Market size — overall scale of the market, ensuring small-but-spiking markets don't crowd out genuinely large ones
  • Related market expansion — whether new sub-markets are forming around the same event, a signal that interest is broadening
Each signal is percentile-ranked within its platform and category before being combined — so a crypto market isn't competing against a politics market on raw volume alone.

The TTR Multiplier

Markets close to resolution get a boost. A Time-to-Resolution (TTR) multiplier is applied on top of the composite score, scaling based on how far through its lifecycle the market is and how few hours remain. The multiplier caps at 1.75× — enough to surface genuinely urgent markets, not enough to let a dying market game the rankings.

Filtering Comes First

Before any market is scored, it passes through an eligibility stack:
  • Stale markets (no meaningful activity) are removed
  • Markets outside their active lifecycle window are excluded
  • A minimum volume floor is applied — set at the higher of the 20th percentile threshold or $1,000. Markets under 12 hours old get a grace period on the volume floor only; price and velocity requirements still apply.
  • Duplicate sub-markets for the same event are deduplicated — only the highest-scoring representative surfaces
After scoring, markets are further deduplicated by parent event. The result is a ranked list of up to 25 events — reflecting real attention, not random noise.

Breaking Markets

The Breaking category surfaces markets where something has already happened — a sudden price shift, a surge in volume, or an imminent resolution. It is not a forecast. It is a signal that the market just reacted to something.The three signals and their weights
  • Price shock — the magnitude of a recent price move, measured in percentage points. A market that moved 25 points in a short window scores significantly higher than one that drifted 3 points over a day.
  • Volume surge — 24-hour volume compared to the prior 24-hour period. To prevent extreme outliers from distorting the rankings, the raw percentage change is capped at 5,000% before scoring.
  • Urgency — proximity to resolution. A market resolving tomorrow scores materially higher than one resolving in six days.
All three signals are percentile-ranked across the full breaking pool before being combined — not within platform or category buckets. A political market and a crypto market compete on equal footing.

The Size Modifier

After the base score is computed, a soft size modifier is applied. Larger markets (by total volume) receive a modest upward adjustment — capped so that market size never overrides signal strength. The modifier is intentionally subtle: it's a tiebreaker, not a deciding factor.

Eligibility Filters

Breaking has a tighter eligibility gate than Trending. Markets must pass all of the following to enter the pool:
  • Not resolved
  • At least 0 days remaining (not expired)
  • No more than 7 days remaining — Breaking is a short-horizon feed
  • A minimum price shock of 10 percentage points
  • A positive volume surge (stable, post-clip) above 50%
  • Minimum $1,000 in total volume — waived for markets under 12 hours old, though price shock and volume surge requirements still apply
  • Deduplication — markets grouped by series; the highest scorer per group advances

Real-Time Render Guards

Scoring runs on a set cadence. But markets can resolve, expire, or enter dispute between runs. PredictionHero applies a second eligibility check at the moment of display — evaluated against live data, not cached scoring fields. A market that resolved after the last scoring cycle will never appear in the Breaking feed.The result is a feed of up to 15 markets — the ones where something is genuinely happening right now.

Prediction Market Dashboards

PredictionHero’s Dashboards system is designed to surface high-signal prediction market activity across categories, platforms, and time horizons.Rather than requiring users to manually scan thousands of individual markets, dashboards organize real-time prediction market data into curated discovery views focused on momentum, volatility, activity, and emerging narratives.Dashboards are intended to help users quickly identify:
  • trending prediction markets
  • breaking market activity
  • rapid probability shifts
  • unusual trading behavior
  • major gainers and decliners
  • and cross-category market movement
Dashboard rankings and signals are generated dynamically using market activity, liquidity, price movement, and participation data aggregated across supported platforms.

Biggest 24-Hour Gain

The Biggest 24-Hour Gain dashboard highlights markets with the largest positive probability movement over a rolling 24-hour period.This may reflect:
  • new information entering the market
  • rapid sentiment changes
  • major news developments
  • or repricing events
Large upward moves do not necessarily indicate accuracy or inevitability. They indicate that market participants have rapidly reassessed probabilities over a short period of time.

Biggest 24-Hour Drop

The Biggest 24-Hour Drop dashboard highlights markets with the largest negative probability movement over a rolling 24-hour period.These markets may reflect:
  • failed narratives
  • changing expectations
  • breaking counter-information
  • or reversal events
Sharp downward moves can occur rapidly during periods of elevated uncertainty or news volatility.

Dashboard Ranking Methodology

Dashboard rankings are generated using a combination of:
  • probability movement
  • trading volume
  • liquidity changes
  • activity acceleration
  • market size
  • short-term volatility
  • and relative market participation
Different dashboards may apply different weighting systems depending on the objective of the ranking category.PredictionHero may also apply filtering systems designed to reduce:
  • spam-like activity
  • illiquid contracts
  • inactive markets
  • structurally low-signal events
  • or temporary anomalies

Real-Time Dashboard Updates

Dashboard rankings update dynamically throughout the day as new market activity occurs across supported prediction market platforms.High-activity markets may refresh as frequently as every 60 seconds depending on:
  • source platform update frequency
  • API availability
  • and market activity levels
During major geopolitical, political, sports, crypto, or macroeconomic events, dashboard rankings may change rapidly as prediction market sentiment evolves in real time.

Dashboard Limitations

Dashboard rankings are designed to improve market discovery and situational awareness, but they should not be interpreted as investment recommendations or guarantees of market accuracy.Certain dashboard movements may be influenced by:
  • low liquidity
  • temporary volatility
  • news-driven reactions
  • or platform-specific pricing inefficiencies
PredictionHero attempts to surface meaningful market signals while preserving transparency around market limitations and platform constraints.

Data Freshness & Update Frequency

PredictionHero dynamically updates market data based on platform availability, activity levels, and infrastructure constraints.High-activity markets may refresh as frequently as every 60 seconds, while lower-volume markets may update less frequently depending on source platform limitations and API availability.Update frequency may vary between platforms.

Known Constraints

Some prediction market platforms may experience:
  • delayed reporting
  • temporary API outages
  • stale liquidity metrics
  • inconsistent update intervals
PredictionHero attempts to surface the most accurate and current prediction market data available while clearly preserving source-platform limitations.

Prediction Market Data Limitations

Prediction markets are powerful forecasting systems, but they are not perfect.

Known Limitations

  • liquidity varies significantly across platforms
  • some markets are thinly traded
  • data delays can occur
  • resolution criteria may be ambiguous
  • markets can become temporarily inefficient
  • platform incentives may differ
  • pricing may react emotionally during major events

What This Means

Prediction market prices reflect beliefs, incentives, and available information under real-world constraints.They should not be interpreted as guarantees or objective truth.PredictionHero is designed to improve transparency and comparability—not eliminate uncertainty.

What PredictionHero Does NOT Do

PredictionHero does not:
  • execute trades
  • provide financial advice
  • influence market outcomes
  • modify source platform probabilities
  • determine event resolution
  • guarantee pricing accuracy
PredictionHero is an intelligence and aggregation layer built on top of external prediction market platforms.

Research & Methodology Approach

PredictionHero combines:
  • real-time prediction market aggregation
  • statistical normalization
  • semantic market matching
  • rule-based analysis
  • and cross-platform comparison systems
to improve prediction market transparency and usability.The platform is designed to preserve platform-specific distinctions while enabling structured comparison between markets that may otherwise be difficult to evaluate side-by-side.

Frequently Asked Questions

What is a prediction market aggregator?

A prediction market aggregator collects and standardizes prediction market data from multiple platforms into a single interface for comparison and analysis.

How does PredictionHero differ from Polymarket?

Polymarket is a prediction market platform where users trade contracts directly. PredictionHero aggregates and analyzes markets across multiple platforms, including Polymarket.

How does PredictionHero differ from Kalshi?

Kalshi is a regulated event exchange focused on forecasting contracts. PredictionHero aggregates data across multiple platforms and provides cross-platform comparison tools, filtering systems, and Resolution Divergence Alerts.

How often does PredictionHero update market data?

High-activity markets may update as frequently as every 60 seconds depending on platform availability and API constraints.

How are prediction market probabilities calculated?

Prediction market probabilities are generally derived directly from market prices. A Yes price of $0.70 corresponds to a 70% implied probability.

What is prediction market consensus?

Prediction market consensus refers to an aggregated probability view generated from multiple markets referencing the same real-world event.

Why do prediction market odds differ across platforms?

Differences may result from:
  • varying user bases
  • liquidity differences
  • platform-specific incentives
  • resolution rule differences
  • and information asymmetry

What is a Resolution Divergence Alert (RDA)?

RDA is a PredictionHero system designed to identify situations where markets that appear similar may resolve differently due to differing rules or timing conditions.

Does PredictionHero use AI?

Certain classification, matching, and analytical systems may incorporate automated semantic analysis or AI-assisted processing to improve market organization and comparability.

Can prediction markets be manipulated?

Low-liquidity markets may be more vulnerable to temporary pricing inefficiencies or manipulation attempts. Higher-liquidity markets are generally more resistant due to broader participation.

Which prediction markets are most liquid?

Liquidity varies significantly by platform, category, and event. Major political, crypto, and macroeconomic markets typically exhibit the highest liquidity.

Are prediction market probabilities accurate?

Prediction markets can be highly effective forecasting systems, particularly in liquid markets. However, probabilities reflect market consensus rather than certainty.

Does PredictionHero allow trading?

No. PredictionHero does not execute trades or custody user funds. The platform links users to external prediction market venues.

Methodological Principles

PredictionHero is designed around several core principles.

Source Fidelity

Market data should reflect the original source platform as accurately as possible without reinterpretation or manipulation.

Transparency

Users should be able to understand how prediction market probabilities, rankings, and consensus calculations are generated.

Cross-Platform Comparability

Prediction markets from different platforms should be standardized in ways that preserve meaningful structural distinctions while enabling useful comparison.

Clear Disclosure of Limitations

Prediction market limitations, liquidity constraints, and resolution ambiguities should be disclosed whenever possible.

Neutral Presentation

PredictionHero does not take positions on market outcomes and does not attempt to influence prediction market sentiment or event resolution.

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PredictionHero © 2026 · v0.13.0PredictionHero provides aggregated market data and informational signals only. Nothing on this site constitutes financial, legal, or investment advice. Markets are volatile and speculative. Past performance does not guarantee future results. Always do your own research and consult qualified professionals before making decisions involving risk.