When the same MLB game trades on both Polymarket and Kalshi, the two prices move almost in lockstep — they correlate 0.996. But "almost" is where the interesting question lives: when they do move, which venue moves first? Which book is leading price discovery, and which is following?
On the data we have, the answer is consistent and survives three independent tests: Polymarket leads, Kalshi follows. Here's the evidence, the replication, and — just as importantly — why this does not hand you a trade.
The result
We took a matched book of 26–29 settled MLB games over 3 contiguous days (June 21–23, 2026; ~57K snapshots, ~31-second median sampling) and looked at "follow events": moments where one venue's mid moves while the other is momentarily flat. The question is simply which venue tends to be the one that moved.
- Polymarket leads 63.6% of follow-events (p < 1e-6).
- The direction replicates every single day: 0.657 / 0.667 / 0.635 across the three.
- Three independent methods agree:
- Granger cross-coefficient asymmetry of 3.8× (0.46 vs 0.12)
- lagged cross-correlation 0.296 vs 0.072
- per-game clustering: 25 of 26 games show Polymarket leading (Wilcoxon p < 1e-4) — so this is not an autocorrelation artifact riding on one or two noisy games.
When three different lenses — event-based, regression-based, and per-game — all point the same way and the effect reproduces day over day, that's about as solid as a small-sample microstructure result gets. We later re-ran the question on a sixteen-day window — the follow-up lead-lag study found the same direction on all sixteen days.
What about which venue is right?
A natural follow-up: if Polymarket moves first, is Kalshi the more accurate of the two (since it has the extra beat to incorporate information)? The data hints at this — Kalshi's level is fractionally closer to the final settlement — but the honest reading is that this half is weak and we won't headline it:
- the per-game-team accuracy gap is only 0.125¢ (Brier difference 0.0013),
- the paired t-test is p = 0.056 — not significant at the conventional 0.05 bar,
- and it does not replicate: drop June 23 and the tally flips to 12 Kalshi-closer / 13 Polymarket-closer. The entire "accuracy edge" is essentially carried by a single day.
So: lead-lag, strong and replicated. Accuracy, a marginal hint we're flagging as not yet established. We'd rather tell you which is which than blur them together.
Why you can't trade this
This is the part a less honest write-up would leave out. A 1¢ lead is not a 1¢ profit. To capture Polymarket's first move you'd have to cross 3–5¢+ of round-trip cost, and the accuracy difference is sub-cent. The lead exists; the edge does not survive the friction.
Our own bot is the proof. Even trading these markets directionally, it runs negative closing-line value (−6.7¢ at settlement), −5.7% live ROI, and +2.2¢ slippage — break-even-to-negative on a market we've separately measured as efficient and well-calibrated. Knowing who moves first is genuinely interesting microstructure. It is not a money printer, and we won't pretend it is. What we sell is the data, not a signal.
What we're not claiming
- N = 26–29 settled games over 3 contiguous off-season MLB days, one capture window (with a known Apr 22–Jun 14 gap).
- The ~31-second median sampling floor means this is a 30–90-second-horizon statement, not a microsecond price-discovery claim. The true race is almost certainly faster than we can see; we can only say Polymarket has already moved by the time we next observe Kalshi.
- We track one team/side per game — we see half of each market.
- Granger t-statistics are inflated by pooled autocorrelation, so the load-bearing evidence is the 3.8× coefficient asymmetry plus the per-day and per-game replication, not raw t-values.
See for yourself
The free, score-synced matched-book sample — both venues on one timeline, winner labeled — is on Hugging Face and Zenodo (DOI 10.5281/zenodo.20816908). It has everything you need to rerun the lead-lag test yourself.
For the capture methodology, see how to get historical Polymarket order-book data, and if you're weighing all the sources — us included — start with our comparison of where to get historical Polymarket and Kalshi order-book data. To reproduce this cross-venue result, inspect the Polymarket–Kalshi MLB matched book.