The Sims Vs Kalshi Ledger: Every Call, Graded In Public

This ledger exists to answer one question about our Sims vs Kalshi coverage: how has it actually done? Every day, the Kalshi MLB picks page and the home run edge board publish the places where Stokastic's simulations disagree with Kalshi's live prices. Every one of those disagreements lands here the same day, and gets graded against the exchange's own settlement when the games end. Nothing is removed, nothing is regraded, and the misses stay up with the hits.

The Quick Answer

Each row below is one published call: the date it appeared, what the Sims said, what the market priced, the gap between them, and how Kalshi settled it. The grading rule is mechanical, settlement only, so every row can be audited against Kalshi's public results. The full running table and how to read it are below.

The Ledger

As of September 17, 2026 at 3:21 PM ET — 3 call(s) pending settlement, 0 newly graded this run.

The Rules This Ledger Runs On

Recorded at publish, not after. A call enters the ledger the day it appears on a live page, with the numbers it was published with. There is no way to add a call retroactively, because the entry is written by the same automated run that publishes the page.

Settlement is the only grader. When Kalshi resolves a contract yes or no, that result is copied onto the entry. A home run gap that pointed positive "hits" when the contract settles yes; a negative gap hits when it settles no. Game rows grade on whether the team the Sims' run edge favored won the contract. No human touches a grade.

Misses are the point. A projection engine that never missed would be a broken market, not a good model. What the ledger measures is calibration: when the Sims and a regulated market disagree by several points, how often is each side right? That number, tracked over hundreds of rows, is worth more than any single day's picks, and it is the number this page is built to accumulate.

Pending means pending. Contracts that have not settled show as pending, not as wins in waiting. Postponed games stay pending until Kalshi resolves their markets, however it resolves them.

How To Audit A Row Yourself

Every row names its market implicitly through the date and the call, and Kalshi publishes every settlement on its own site. Take any graded row, find the matching contract on Kalshi for that date, and check the result. If our grade and the exchange's result ever differ, something is broken and we want to know about it. The audit takes about a minute per row, which is the point: a record you cannot check in a minute is not really a public record.

A Worked Example Of What Calibration Means

Say the board publishes a hitter at 20% from the Sims against a 12c market, an 8 point positive gap. One row settles once and proves nothing, a home run either happens or it does not. But suppose 50 rows like it accumulate over a month. If those hitters homer at roughly a 20% clip, the Sims were right and the 12c prices were cheap. If they homer at closer to 12%, the market was right and the simulated number ran hot. If the truth lands near 16%, both sides were part right, which is the most common outcome between a good model and a liquid market. The ledger exists to let that arithmetic happen in public instead of in a marketing claim, and the same logic applies symmetrically to negative gaps, where we publish that the market is paying more than the simulations support.

What we expect, honestly: most days, the market and the Sims will agree within a few cents, and most graded disagreements will split somewhere between the two numbers. If the record shows the Sims consistently beating the market in a spot, that is interesting. If it shows the reverse, that stays published too.

The Buckets The Record Will Report In

Raw hit rates mislead when prices vary, a 45c favorite settling yes tells you almost nothing, while a 8c longshot doing it is a real event. So as rows accumulate, the ledger reports calibration inside price buckets, and the buckets are fixed now, before any results exist, so they cannot be gerrymandered later.

Longshots, 1c to 12c. A 8c home run contract implies 8%. If the Sims' positive gaps in this bucket settle yes at 15% over a real sample, the Sims found something; at 8%, the market had it right all along. This bucket accumulates fastest because most home run contracts live here.

The middle, 13c to 30c. Where the everyday power hitters price, a 20c contract implying 20%, and where the Sims' edge, if it exists, should be most visible: the simulation has lineup-lock information and the book has traders, and the two disagree here more often than anywhere else.

Favorites, 31c and up. Mostly game-winner rows and the occasional hot hitter at 35c or better. Small sample, watched mostly for symmetry, because a model that only finds value in longshots is usually a model with a longshot bias rather than an edge.

Sample sizes gate everything: no bucket gets a headline number before 30 graded rows, and every bucket's row count publishes next to its rate. Our fantasy coverage applies the same simulation engine to season-long markets on the fantasy football prediction markets page, and those calls will join this ledger when the NFL lanes turn on.

What This Is Built From

The Sims side of every row comes from the Stokastic MLB Sims, the simulation engine behind our DFS projections: thousands of simulated games per slate, at-bat by at-bat, with confirmed lineups and tonight's actual starters. The market side comes from Kalshi's live order books, fetched and stamped by the same run that writes the pages. If you are new to reading exchange prices, where a 40c contract means a 40% market probability and a 12c contract means 12%, our sister site's Kalshi guide is the place to start. And the same simulation engine, pointed at DraftKings slates instead of exchange contracts, powers the daily MLB DFS picks page.

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