Market Calibration by Platform and Price Bucket, 2024–2026

Kalshi Tracks the Diagonal Closest at the Extremes

Weighted by market count, Kalshi's price and its observed YES rate differ by 3.86 percentage points on average across its 20 buckets. At the two extremes — 0-5% and 95-100%, which together hold most of the sample — the gap shrinks to 1.16 points, matching the pattern that markets are re-priced most carefully right before they become nearly certain.

The widest single gap is the 40-45% bucket: markets there closed at an average price of 42.32% but only resolved YES 18.18% of the time, a 24.14-point overconfidence gap in the messiest, least-certain part of the range. Manifold's equivalent weighted average gap is 3.03 points, wider than Kalshi's — consistent with, though not proof of, the real-money-vs-play-money difference explained below.

Kalshi Calibration Curve, 2026

Each dot is one 5-point Kalshi price bucket; dot size scales with the number of markets in the bucket. The dashed line is perfect calibration (price = observed rate). Hover a dot for the bucket's numbers.

Full Calibration Table

gap_pct = avg_close_price_pct − observed_yes_rate_pct; positive means the price overstated YES.

Download the full table (CSV) · 80 rows

How the Numbers Were Made

Price is Kalshi's last traded price before settlement or Manifold's probability field on a resolved binary market. Only markets with nonzero trading volume and a definite YES/NO result are kept; 5-point buckets are floor(price×20)×5, so a 47.9% close falls in the 45-50 bucket.

Kalshi is real money; Manifold is play money. Kalshi settles contracts in U.S. dollars under CFTC oversight; Manifold runs on a fake in-app currency ('mana') with no cash value. The two platforms are shown side by side because they are the only ones with a usable, non-circular price-to-outcome record (see below), not because their numbers are directly comparable — a Manifold bettor risking play money has different incentives than a Kalshi trader risking cash, and that difference is a known, plausible explanation for any gap between the two.

Kalshi shows 2026 only: direct year-filtered API probes returned 0 settled markets for 2021-2023, and the 2024 (68 markets) and 2025 (26 markets) settled markets that do exist all had a last price and volume of exactly 0.00 simultaneously — read as unpopulated older records rather than a genuine zero, so the volume filter drops them. Kalshi's settled-market index behaves like a rolling recent window, not a full historical archive, at least via this public endpoint.

Polymarket is not in this table. Its public Gamma API caps the reachable sample at roughly 2,100 closed markets, almost all from 2020–2022, before Polymarket's central-limit order book existed. On those markets the only price field available is the final settlement value (effectively exactly 0 or 1), not a pre-resolution trading price, and the CLOB's price-history endpoint returns no data for them. Using that field as a "forecast" would be circular — it would compare the outcome to itself — so Polymarket is left out rather than faked.

Sources

1. Kalshi public API (/markets, /series)primaryKalshi · primary · retrieved 2026-09-13 · Public API, no key required. Terms at https://kalshi.com/terms-of-use
2. Manifold public API (/v0/search-markets)primaryManifold Markets · primary · retrieved 2026-09-13 · Public API, no key required. Terms at https://manifold.markets/terms