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Streaming Polymarket and Kalshi Order Books over WebSockets: 7 Lessons from Production

Dozor | Esports Surebet Scanner — Sat, 10 Oct 2026 14:00:00 +0000

We run a live arbitrage scanner that prices esports markets on Polymarket and Kalshi against 25 sportsbooks. Both exchanges are read through WebSocket order-book channels in Go (gorilla/websocket). A wrong top-of-book here is not a cosmetic bug: the price becomes decimal odds, the odds become an arb, and the arb is someone's real money. These are the lessons that cost us the most to learn.

1. On Polymarket, trust the server's best bid/ask, not the book you rebuilt

Polymarket's public /ws/market channel sends a book snapshot and then price_change deltas that also carry the server's best_bid/best_ask. The obvious design is to apply deltas to a local book and read the top of it. We measured that on a live channel — 1,200 tokens, 5 minutes, 24.6k deltas:

About 1% of deltas left our locally rebuilt book with a different top-of-book than the server reported, and the divergence was sticky — it did not converge by itself.
We checked who was right by forcing a fresh snapshot: of 106 divergences, the new book confirmed the server's best in 87 cases and our local book in one.

So the price comes from the server's best_bid/best_ask, and the divergence itself became a desync detector: if levels disagree with the server, depth from that book is not trusted and the book is rebuilt.

2. Resync by unsubscribe + subscribe — a plain re-subscribe does nothing

To rebuild one token's book we unsubscribe and subscribe it again; the server sends a fresh book in 89 ms on average (119 ms max). Re-subscribing without unsubscribing first does not work: the channel answers with the text NO NEW ASSETS and sends no snapshot.

Resyncs are batched (every 500 ms, at most 200 tokens per tick) with a per-token cooldown, so a burst of divergences cannot turn into a storm of subscription frames. One more limit we hit: a subscribe/unsubscribe message carries at most 500 asset IDs; anything past that is dropped without an error.

3. Know who answers your heartbeat

On Polymarket, protocol-level ping frames are answered — but by the Cloudflare edge, not by the origin. A dead stream behind a live edge keeps answering control pings, so a read deadline extended by those pongs would keep a frozen book "alive". We use the channel's application-level heartbeat instead: a text PING every 10 s, a text PONG back from the channel itself, and a 30 s read deadline. Writes get their own 5 s deadline — without it, a full send buffer hangs the book forever and silently.

4. On Kalshi, server pings must extend your read deadline

Kalshi does the opposite: the server sends control pings every 10 seconds, and those pings are the sign of a live channel. Our read loop extended the 30 s deadline only on data frames. gorilla/websocket's default ping handler replies with a pong but does not touch the read deadline.

Most of the week that did not matter — order books change often enough. Then, every Thursday during Kalshi's maintenance window (07:00–09:00 UTC, when trading pauses), books stop changing, and the connection dropped every 30–80 seconds with i/o timeout. Each reconnect cleared the cache and re-fetched about a thousand snapshots. It was not a regression; it had happened every Thursday since we moved Kalshi to WebSockets. The fix is four lines:

pong := conn.PingHandler()
conn.SetPingHandler(func(appData string) error {
    _ = conn.SetReadDeadline(time.Now().Add(readWait))
    return pong(appData)
})

A downstream guard that holds the last good snapshot when a book suddenly empties kept the drops off users' screens — which is also why it took weeks to notice.

5. Kalshi's `seq` is per subscription, not per market

We subscribed orderbook_delta to 30 tickers at once. The 30 orderbook_snapshot messages arrived with seq 1 to 30, and every delta after that, across all tickers, continued one shared sequence (31, 32, 33…). A gap in seq therefore means the whole subscription is suspect: we rebuild the subscription, not one market. Partial recovery would be a guess, not documented behaviour.

The WebSocket handshake is signed: an RSA-PSS signature of timestamp_ms + "GET" + "/trade-api/ws/v2" in the KALSHI-ACCESS-* headers. An unsigned request gets 401.

6. Use WebSockets only where they pay off

Measured traffic on Kalshi: 30 tickers produced 158 deltas in 25 s — 6.3 messages/s, about 0.2 per ticker. For the ~640 open esports markets that day, that extrapolates to roughly 135 messages/s in one subscription on one connection, far from needing sharding.

Market structure is a different story. market_lifecycle_v2 cannot be filtered by ticker, so it streams the lifecycle of the whole exchange — weather, politics, economics — and its messages carry no tag that says "esports". We kept structure on REST (/series?category=Sports, then /events per series, refreshed every 15 s) and moved only the order books to WebSockets, which is where the REST budget was going.

7. Decimals, stale books and one reconnect loop

Decimals, not floats. Odds are computed as 1/best, so a rounding error becomes a phantom arb. Prices are compared as decimals, not strings: the server does not guarantee the same text for one price in a snapshot and in a later delta.
A stale book is worse than none. On disconnect we drop the books instead of keeping them. For Polymarket the scanner then falls back to the slower Gamma listing price until fresh snapshots arrive; a frozen book would quote prices that no longer exist.
One reconnect loop for everyone. Polymarket, Kalshi and a third WebSocket book each had their own copy of the lifecycle and backoff code (1 s, doubling to 30 s). A fix in one copy did not reach the others, so they now share one package.

What this feeds

These caches feed a canonical market model shared with the sportsbook adapters; a matcher maps the same match across 27 books, and a server-side engine recomputes arbs on every cycle, net of each market's exchange fee. The data side of the project is in our previous post, Polymarket & Kalshi Arbitrage vs Sportsbooks: 30 Days of Esports Data. The scanner itself: prediction market arbitrage; the price conversion it relies on: odds converter.

Dozor is an esports arbitrage scanner covering 25 sportsbooks plus Polymarket and Kalshi. It is an information tool, not a bookmaker. 18+.

Polymarket & Kalshi Arbitrage vs Sportsbooks: 30 Days of Esports Data

Dozor | Esports Surebet Scanner — Tue, 06 Oct 2026 13:51:39 +0000

TL;DR. Over 30 days (Sep 6 – Oct 6, 2026) our scanner logged about 4.87 million arbitrage opportunities in esports across 27 books: sportsbooks, crypto sportsbooks and two prediction markets, Polymarket and Kalshi.

About 1 in 6 arbs (15.9%) had a Polymarket or Kalshi leg. Polymarket alone appeared in 642,253, Kalshi in 138,017.
Arbs between Polymarket and Kalshi themselves are rare: 4,435 in a month, 0.09% of all arbs. The other side of a prediction-market arb is almost always a sportsbook.
Arbs with an exchange leg last longer. In live play, 23.9% of them survive 10 seconds or more, versus 14.4% for sportsbook-only arbs. The median lifetime of a Polymarket arb is 4.1 s, twice the overall 2.0 s.
In prematch, exchange arbs pay more: median ROI 2.30% versus 1.54% for sportsbook-only.

Below: the dataset, how we measured it, the tables, and a short look at the pipeline that produces the numbers.

What counts as an arb

An arbitrage (a "surebet") is a set of bets on every outcome of the same market, placed at different books, where the implied probabilities add up to less than 1:

1/k1 + 1/k2 < 1          ROI = 1 / (1/k1 + 1/k2) - 1

Example: Team A to win the match at 2.10 on a sportsbook, Team B to win at a price that converts to 2.05 decimal on Polymarket (a 48.8¢ share). 1/2.10 + 1/2.05 = 0.964, so the arb returns about 3.7% whatever the result. Prediction-market prices are probabilities, so they need converting first: odds converter, surebet calculator.

Dataset and method

Window: 30 days, Sep 6 – Oct 6, 2026.
Coverage: esports only — CS2, Dota 2, League of Legends, Valorant, Rainbow Six and smaller titles. 25 sportsbooks and crypto sportsbooks plus Polymarket and Kalshi. Full list with per-book stats: bookmakers.
Lifetime of an arb = last time it was seen minus first time it was seen. All books are read at the same time and every arb is recomputed on each cycle, so lifetime has a resolution of about 2 seconds.
ROI = the best ROI the arb reached during its life.
Caveats. The set of books changed during the window, so daily volumes are not a market trend. A slower scanner sees fewer short-lived arbs and a longer median. An arb seen in a single snapshot is often a timing difference between two quotes rather than a real mispricing — which is why we show price age on every leg.

Finding 1: prediction markets are in 1 of 6 arbs

	Arbs, 30 days	Share of all arbs	Live	Prematch
All books	~4.87M	100%	81%	19%
With Polymarket	642,253	13.2%	64%	36%
With Kalshi	138,017	2.8%	65%	35%
Polymarket + Kalshi together	4,435	0.09%	—	—

Two things stand out. Exchanges are relatively stronger in prematch: a third of their arbs happen before the match starts, versus a fifth across all books. And Polymarket and Kalshi rarely disagree with each other on esports — when they are mispriced, they are mispriced against sportsbooks. If you are looking for "Polymarket vs Kalshi arbitrage" in esports, the volume is on the prediction market vs sportsbook side.

Finding 2: exchange arbs live longer

Arb type	Mode	Median life	90th percentile	Lasting ≥10 s	Lasting ≥60 s	Median ROI
Sportsbooks only	Live	2.0 s	14.2 s	14.4%	1.2%	3.37%
With an exchange leg	Live	2.0 s	24.4 s	23.9%	2.9%	3.09%
Sportsbooks only	Prematch	14.1 s	93.5 s	55.9%	17.8%	1.54%
With an exchange leg	Prematch	10.3 s	177.4 s	51.7%	17.3%	2.30%

In live play the median is the same, but the tail is much fatter: an arb with a Polymarket or Kalshi leg is 1.7x more likely to survive 10 seconds and 2.4x more likely to survive a minute. Across both modes, 44.6% of exchange arbs live 5 seconds or more, versus 29.7% for sportsbook-only arbs.

By book, the median lifetime is 4.1 s for Polymarket and 4.0 s for Kalshi, against 2.0 s for all arbs. Arbs lasting a minute or more make up 8.3% of Polymarket arbs and 6.9% of Kalshi arbs, against 4.5% overall. Per-book pages: Polymarket, Kalshi.

Our reading (a hypothesis, not a measured cause): sportsbooks reprice esports lines with trading teams and feeds, while exchange prices move only when someone trades. A stale order sits in the book until it is taken.

Finding 3: the pairs that produce them

Pair	Arbs	Lasting ≥60 s	Median life	Median ROI
Olimp – Polymarket	135,476	7,738	6.1 s	2.81%
Duel – Polymarket	80,260	11,062	4.2 s	1.96%
1xBet – Polymarket	69,719	5,437	4.0 s	2.96%
BetBoom – Polymarket	39,014	3,849	6.4 s	3.91%
Marathon – Polymarket	37,755	2,575	6.1 s	3.47%
Kalshi – Olimp	25,469	1,413	4.2 s	2.82%

All pairs with daily-updated stats: pairs.

Finding 4: which esports titles

CS2 dominates everywhere, but exchanges lean towards slower titles. League of Legends is 18% of Polymarket arbs and 26% of Kalshi arbs, against about 7% across all books. Dota 2 is 20% of Polymarket arbs. Slower games mean fewer price jumps per minute, which fits the longer lifetimes above. More on titles: esports arbitrage, live vs prematch.

How the pipeline works

For the developers reading this, a short version of what produces these numbers:

One adapter per book. Each sportsbook is read by its own process (Python) and normalized into a canonical market model: (kind, scope, line) — match winner, map winner, handicap, total, rounds, kills.
Prediction markets in Go. Polymarket markets are discovered through the Gamma API and priced from the CLOB WebSocket order book; Kalshi comes in through its REST API and the v2 WebSocket feed. Exchange prices are converted from probabilities to decimal odds before they meet sportsbook lines.
Event matching. The same match has different names, IDs and start times on 27 books. A matcher (Go) resolves them into one event using team-name normalization, tournament rules and a rules file that humans and strong automatic evidence can update.
Server-side arb engine. Arbs are computed in one place, on the server, for every matched market on every cycle. When an arb disappears, its first/last seen time, max ROI, market kind and books go into a history table — the source of this article.
Delivery. The browser gets a compact WebSocket stream with ROI, the age of every quote and a direct link to the event, because in live play the question is not "is there an arb" but "is it still there".

Practical notes

Liquidity is the limit on exchanges. Polymarket and Kalshi do not limit winning accounts, but an arb is only as large as the depth at the quoted price.
Fees and withdrawals differ. See Polymarket fees and withdrawal and Polymarket or a bookmaker.
Sportsbooks limit arbers. The exchange is often the leg that stays open longest; the sportsbook leg is the one that gets restricted.
Check quote age before you click. A 10% "arb" is more often a stale line than a gift.

Step-by-step guide: how to arbitrage Polymarket and Kalshi. Lifetime study across all books: how long do surebets last.

Data from Dozor, an esports arbitrage scanner covering 25 sportsbooks plus Polymarket and Kalshi; free plan without a card. Dozor is an information tool, not a bookmaker. 18+. Betting involves risk of loss, and sportsbooks may restrict arbitrage accounts.