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How to Choose a Kalshi and Polymarket Analytics Tool in 2026

Choose a prediction-market analytics tool by testing the quality of its records and calculations against your own trades. A useful comparison starts with fills, fees, contract rules, timestamps, and missing-data handling; no product label proves those records are accurate.

Kalshi notes that fees can differ by market and that maker fees can apply to executed resting orders.[2] Polymarket market and outcome definitions should likewise be checked against its documentation and the specific contract rules.[3]

Seven checks before choosing a tool

  1. Fill and cost-basis fidelity. Keep executed side, quantity, price, fees, partial fills, and cost basis so realized P&L can be reconciled.
  2. Market-native price semantics. Preserve each venue's contract IDs, outcome, payout, and settlement rules. A contract price is not a sportsbook line.
  3. Sourced and timestamped reference data. Identify where a market price came from and when it was observed. A later quote must not be used as an at-fill estimate.
  4. Explicit coverage gaps. Show absent prices or independent fair-probability estimates as missing, with coverage counts. Do not silently fill them with zero.
  5. Portfolio exposure and realized P&L. Distinguish open marks from settled profit, then group positions by market, venue, and related event risk.
  6. Model-assumption visibility. Separate venue data from a user's or model's estimated probability, and expose the assumptions behind EV and Kelly sizing.
  7. Exportability and privacy. Confirm you can inspect or export your records and understand how connection credentials and trading history are handled.

How to evaluate Evrai

Evrai offers Kalshi and Polymarket position tracking alongside sportsbook records, with connected sync or manual logging, bankroll and exposure views, and decision tools. Features and plan access are listed on the pricing page. For Fair Value Spread to be meaningful, an independent estimate must exist at or before the fill; otherwise coverage should remain missing. See the methodology for definitions and limitations.

Test any provider with a small sample: reconcile a fill and fee, an open position, and a settled position against the source venue. Then check whether you can tell sourced prices from model estimates and export your decision record.

Frequently asked questions

How should I choose a Kalshi analytics tool?

Check whether it retains contract side, actual fills, fees, cost basis, settlement, timestamps, and coverage gaps. Compare those records with your own reporting needs and privacy requirements.

How should I choose a Polymarket analytics tool?

Check wallet and market identification, executable prices, fees, position cost basis, and whether estimated fair values are independent and available at fill time. Ask how missing data is shown.

Can one tool cover Kalshi and Polymarket?

Some tools, including Evrai, support both venues. Test the import and manual-entry paths, then verify a sample of positions and realized P&L against each venue before relying on portfolio totals.

Does positive Fair Value Spread prove an edge?

No. It is a comparison with an independent probability estimate available at fill time. Model quality, costs, coverage, and a meaningful sample all matter; realized results are a separate measure.

Sources

  1. Fees — Kalshi Help Center. Reviewed .
  2. What is Polymarket? — Polymarket Documentation. Reviewed .