Correlated exposure

A cap that counts labels does not cap risk. Two names for one underlying cause pass a limit of two, and then fail together.

The 2026-08-21 card

The user: "I'm still not understanding why there are three first five baseball bets as our picks today."

MAX_PER_MARKET = 2 was in place and looked correct. The card had:

Two f5_ml and one f5_total is "2 and 1" against a cap of 2. Every check passed. And all three are one opinion about how the first six outs go: if the starters go deep and quiet, the whole card loses at once. Three tickets, one bet.

The fix is not a smaller number. It is counting the right thing:

MARKET_FAMILY = {
    "f5_ml": "first5", "f5_total": "first5",
    "nrfi": "firstinn", "yrfi": "firstinn", "ttsf": "firstinn",
    "h2h": "fullgame", "totals": "fullgame", "spreads": "fullgame",
}
def _family(m): return MARKET_FAMILY.get(m, m)   # standalone things are their own family

Then apply the cap to the family, everywhere the cap is applied. Missing one path is its own bug: capping straights but not parlay legs is how one market took four of five slots on an earlier card.

Group by what decides the outcome

Not by how the source labels it. The sportsbook files f5_ml and f5_total separately because they are separate tickets, not because they are separate risks. Ask: what single event moves all of these at once?

The same shape elsewhere

• Tests. Twelve tests that all import one fixture are one test with twelve

names. Coverage counts files touched, not failure modes covered.

• Retries. Three retries against the same dead DNS resolver is one attempt.

Today four RSS feeds "failed independently" and three shared one cause: the machine's network was not up at 06:30.

• Sources. Five headlines from five outlets syndicating one wire story is one

data point, and averaging them manufactures false confidence.

• Redundancy. Two availability zones on one power feed. Two API keys on one

exhausted account, which is exactly why the Odds API dying took every soccer result with it.

• Suggestions. Five recommendations all derived from one stale input.

The question

Before trusting any "at most N" or "we have M independent X":

What single thing, if it were wrong, would take all of these down together?

If there is such a thing, your real count is 1, whatever the limit says.