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What you’ll get

The best-ranked price-band rule on Kalshi that has open markets fitting it, and those markets with the ask you would pay, when they close, their liquidity grade and how much rests within 5¢ of the side you would buy. On 2026-09-17 the top Kalshi rule with a match was “buy No when Yes is 60–70¢ a day before close, Culture”, and it had one open match.

Prerequisites

  • An API key in ROUTEUR_API_KEY
  • Python 3 with requests, or Node 18+
1

List the rules, best cautious return first

A strategy is a rule to buy one side of markets priced in a 10-cent band some days before they close, measured over at least 100 settled markets. open_matches says how many listed markets fit it now, above the liquidity floors.
2

Pick the first rule with open matches and list them

The floors are the API’s defaults, written out so they are easy to change: markets that traded at least $1,000 in 24 hours with a round trip of 5¢ or less.
Output observed 2026-09-17 12:48 UTC:
$104 resting within 5¢ of the best No bid is the whole depth behind that 40¢: a $500 order would walk the book.

Read the result

Pitfalls

Returns are historical, before fees, and measured at each band’s average midpoint. The ask in price_usd can be worse. A rule fitted on the history that selected it is not an out-of-sample test, and a 95% range is not a floor. Size positions for being wrong.
  • venue=kalshi and venue=all are different rules. all pools both venues’ settled markets; a rule can be listed under all and not under either venue alone.
  • open_matches counts with the default floors. Pass the same min_volume_usd and max_spread_usd to both requests, or the count and the list will disagree. include_thin=true shows the thin matches, ranked after the tradeable ones.
  • The band is on the Yes price, whichever side you buy. A No rule at band 6 buys No at roughly 30–40¢.
  • Matches are close to the horizon, not exactly on it, and games already under way are left out.
  • Strategies and Calibration: where the rules come from and how honest they are.
  • Liquid opportunities: strategy matches ranked with leads and venue gaps by edge × volume.
  • Slippage at size: what buying $1,000 of a match would actually cost.
  • GET /v1/insights/calibration: how each 10-cent band resolved, the figure a strategy’s return rests on.