A flow-alignment bot for Polymarket’s five-minute BTC Up or Down markets needs three separate inputs: the active market’s outcome-token IDs and live order books, a clearly defined trading signal, and the settlement reference named in that market’s current terms. A spot-price or order-book signal is not proof of a profitable strategy, and a backtest is not credible unless it models executable prices, fills, fees, and the correct settlement method.
What the bot needs to get right first
Each five-minute market is its own contract. Its outcome tokens rotate as windows change, and its resolution terms—not an exchange chart or the bot’s preferred data feed—determine which side pays. The bot therefore needs to rediscover the active market, confirm which token represents Up and Down, read the current terms, and subscribe to those tokens before it can sensibly evaluate or trade a signal.
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Keep three concepts distinct in both code and reporting:
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- Signal: information the strategy uses to estimate the chance of an outcome, such as external BTC prices or changes in displayed order-book depth.
- Settlement reference: the source and method specified by the active market for deciding the result.
- Trading result: the P&L from orders that could actually be filled, after fees, slippage, and any exit or settlement.
A relationship between the first two does not establish the third.
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Which BTC price settles a five-minute market?
Read the active market’s terms
Do not assume that all BTC five-minute markets resolve from a particular exchange’s spot price or that terms seen on one past event apply to every current market. A third-party inspection of one sampled event record quotes a rule naming Chainlink’s BTC/USD Data Stream and describing Up as a price at the end of the title’s time range greater than or equal to the price at its beginning; otherwise, the market resolves Down. The sampled record’s author also notes that its exact snapshot semantics are undocumented. Treat it as an example, not a universal rule.
A Polymarket subreddit moderator announcement says that, effective August 7, 2026, affected crypto five-minute markets would use a 30-second time-weighted average price (TWAP), rather than a single snapshot. The announcement specifies “All crypto 5 min markets: 30 second TWAP.” It does not fully specify timestamps, sample selection, weighting implementation, or exceptions. For a market active now, inspect its own description and the available oracle feed; archive the exact terms and data you relied on for that window.
Polymarket US rules filed with the CFTC describe settlement approaches that can include candlestick measurements, VWAP, TWAP, a simple average, or spot price, and say the contract’s specified source and method control the payout criterion. Those rules provide context for why contract terms matter, but they are US rules—not a substitute for checking the terms of a particular global market.
Keep an external signal separate
A Binance, Coinbase, or other external BTC feed can be a model input, but it is not automatically the settlement series. Differences in source, timestamps, latency, and price construction can matter most near a market boundary. Record the external feed and the named settlement-source data separately so you can measure their basis and timing differences instead of silently treating them as interchangeable.
How to discover markets and receive live book data
Use Polymarket’s official market-data documentation to discover current and upcoming records and obtain the outcome-token identifiers required by its data and trading interfaces. Resolve the current IDs and token-to-outcome mapping from market metadata at each rollover; do not hard-code IDs from an example or a previous window.
Polymarket’s documented market-data WebSocket is wss://ws-subscriptions-clob.polymarket.com/ws/market. Subscribe with the active outcome-token IDs. The feed documents book snapshots containing bid and ask levels, and price-change events containing price, size, side, and best-bid/best-ask fields. Send the application-level PING every 10 seconds and expect PONG. A feed event is evidence of market data, not evidence that one of your orders filled or that the market settled a particular way.
A practical data and execution sequence
- Discover the event and market. Read current market metadata, outcome names, token IDs, start and end times, and resolution description. Save the record and a timestamped copy of the terms used by the bot.
- Subscribe to both outcome books. Request the current Up and Down token IDs, establish the documented heartbeat, and persist snapshots and incremental updates with receipt and source timestamps.
- Validate before enabling orders. Confirm that the feed is fresh, the token mapping matches market metadata, and a usable book snapshot has arrived. If those checks fail, stay in no-trade mode.
- Collect external signals independently. Store the source, source timestamp, receipt timestamp, clock offset, and missing or stale intervals for every external price series.
- Estimate a probability and evaluate executable prices. Compare the estimate with the price and size available at the relevant side of the book; do not use only a last trade or midpoint as the assumed entry.
- Enforce limits and reconcile orders. Track submitted, acknowledged, partially filled, canceled, and settled states. Apply explicit position and loss limits and provide an emergency stop.
- Audit the resolution. Preserve the market record and relevant oracle data, then compare the final outcome with the method and source specified by that market.
This is an engineering workflow, not a tested bot implementation. The official data documentation explains how to subscribe to market data; it does not establish a strategy’s predictive value or guarantee order execution.
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Define “flow alignment” before you test it
The phrase can refer to different hypotheses. For example, a strategy might use signed trade flow, changes in displayed depth, order-book imbalance, or alignment between changes in market-implied probability and an external BTC signal. Those are not interchangeable features. Specify the input, calculation, decision time, and expected direction before looking at outcomes; otherwise it is easy to combine signals after the fact and mistake selection for predictive power.
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For every decision, record at least:
- Market, outcome token, decision timestamp, and time remaining in the window.
- Signal value, source timestamp, receipt timestamp, and data freshness.
- Relevant book state, intended side and order type, executable price, and available size.
- Submitted order, acknowledgement, fills and partial fills, cancellations, fees, and any exit.
- Settlement terms, settlement-source observations, final outcome, and realized result.
Use chronological out-of-sample periods and evaluate market-by-market windows. Prevent look-ahead leakage: a feature available only after the simulated decision time cannot be used to justify that decision. Include simple comparisons such as no trade, a price-only signal, and the market’s own implied probability. These baselines help reveal whether a complex flow feature adds value rather than merely tracking information already in the market.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Model fills and report results honestly
Polymarket’s general FAQ explains that outcome-share prices reflect prices users are willing to trade at and that shares are priced between 0 and 1 USDC. That range does not make the midpoint an executable price. For a simulated buy, use the ask; for a simulated sale, use the bid. If an order consumes multiple levels, account for the depth taken and the resulting average fill. Include the current market-specific fees and plausible slippage; do not assume the last trade or midpoint was available to your order.
Report more than win rate. A useful evaluation includes net returns after costs, maximum drawdown, exposure, number and size of trades, probability calibration by bucket, fill rate, adverse selection, sensitivity to latency, and results by time remaining. State the sample dates and number of observations. Keep paper results separate from live results, and do not combine them into a single performance figure.
The reviewed sources provide API and feed mechanics, not a measured edge or profitability statistic for flow alignment on these markets. Until a strategy has credible, reproducible out-of-sample and live results, describe it as an unproven hypothesis rather than a profitable bot.
Failure modes that should stop or invalidate a trade
Wrong market or outcome token
At every rollover, rediscover the market and validate the token-to-outcome mapping against current metadata. A stale subscription can put a bot on the wrong contract even if its price feed looks active.
Settlement mismatch or changed terms
Archive the market’s resolution text and corresponding source data for each window. Verify the current method rather than substituting an exchange price or relying on a sampled event. Where TWAP is specified, do not invent the averaging timestamps or calculation method from the announced duration alone.
Stale, incomplete, or disconnected data
Detect missed heartbeats, stale timestamps, sequence gaps, and socket disconnects. Pause new orders when state is uncertain; reconnect, resubscribe, and rebuild state from a fresh snapshot before resuming.
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Reject simulations that fill at midpoint or last trade without evidence the order could execute there. Model bid/ask, depth, partial fills, fees, and slippage using the conditions available at the decision time.
Overfitting and operational exposure
Freeze the signal definition before evaluation, use chronological holdouts, compare simple baselines, and disclose weak periods as well as strong ones. Set position and daily loss limits, maintain order-state reconciliation, and use a no-trade mode whenever feed integrity or market terms are uncertain.
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