2026 Member-Member Calcutta

How We're Playing the Auction

A plain-English guide for the buy team — the partners pooling money with Nick. No data-science background needed. By the end you'll know what we're buying, why we trust the numbers, and how we'll behave in the room.

The big idea, in three sentences. We treat the Calcutta like buying stocks: every team has a fair price (what its shot at the flight prize money is actually worth), and we hunt for teams selling below it. We get those fair prices by combining four things — a longtime member's inside knowledge, what teams actually did in past years, a computer that simulates the matches tens of thousands of times, and a form/clutch algorithm as a tiebreaker — stacked in that order of trust. Then we spend our bankroll with discipline: a few strong teams in the flights where the money pools, one team per flight, and cash held back for late bargains.

2How a team makes money

This is the most important rule, because it shapes everything. The Calcutta money is not one big shared pool. It splits two ways:

So a team's value comes almost entirely from how its own flight does — both how likely it is to finish 1st or 2nd, and how much money that flight attracts at auction. A flight that draws heavy bidding has a big pot to pay out; a thin "no bueno" flight pays little even if you win it.

We deliberately ignore the shootout. It's only 10% of the money, it's an overall-winner crapshoot across the whole field, and chasing it would distort our bids. We value teams on flight money only. Winning the shootout would be a free bonus, not part of the plan.

What the flights pay (projected 2026)

Flights are seeded by handicap — Flight 1 is the best players, Flight 20 the highest handicaps. Money concentrates in the low-numbered flights: those teams cost more, so those flights build bigger pots.

Flight tierPot (each)WinnerRunner-up
Top (Flight 1)~$9,700~$6,100~$2,600
Upper-mid (2–6)~$5,400–7,500~$3,400–4,700~$1,500–2,000
Middle (7–13)~$3,200–4,900~$2,000–3,100~$870–1,300
Bottom (14–20)~$1,200–2,900~$760–1,800~$320–780

Total projected pot across all 20 flights: ~$84,000. These are projections to value against, not guarantees — final numbers depend on what sells in the room.

Takeaway: winning a low-flight is worth several times more than winning a high one. That's why we concentrate where the money pools.

3How we estimate each team's win chance

Every flight is six teams, round-robin. Each team plays the other five in a 9-hole, two-man, net better-ball match (best ball of the partners on each hole, with handicap strokes). You earn match points, and the team with the most total points across all five matches wins the flight. Second-most is runner-up.

We can't know who wins — golf is too random. So instead of guessing, we let a computer play the whole event out about 40,000 times (up to 60,000 in the main model). Each run:

  1. Draws a realistic round for every player from their actual last-12-months of scores (via GHIN) — hot, steady, or streaky, each gets a spread matching their real golf.
  2. Adds the shared swings — a hard or easy weather day lifts the whole flight; partners in the same group move together.
  3. Plays all five matches hole by hole, applies handicap strokes correctly, and tallies points.
  4. Records who won the flight and who placed 2nd.

Do that 40,000+ times and you get a clean answer: "this team won the flight in 43% of simulations, placed 2nd in 16%." Those are the team's win and runner-up probabilities — not a hunch, but the box score of 40,000 imagined tournaments.

Why so many upsets? 9 holes is short — not enough holes for the better team to grind out its edge. So even strong favorites usually land around 20–25% to win a six-team flight (a pure coin-flip would be ~17% each). A genuinely dominant team like Wood + Estes (~43%) really stands out, because the format flattens everyone else toward the pack.

Turning that into a fair dollar value is simple once we have the probabilities:

Fair value = (chance to win × winner's share + chance to place × runner-up's share) × that flight's pot

A 43% shot at a ~$4,000 flight is worth real money; a 12% shot at a $2,500 flight is worth very little. Every team on our board gets a fair value this way, which we compare to what we expect it to actually sell for. The gap — the "edge" — is what we shop for.

4The four data sources — most to least trusted

The model is powerful, but it only knows handicaps and posted scores. It's blind to sandbagging, temperament, and who's actually won when it mattered. So we stack four sources, and when they disagree, the higher one wins.

The stack in one line: Jason's read and the record book tell us where the model is wrong; the model tells us the price; Cap Patrol just nods along.

We also run a matchup check — a round-by-round look at each favorite's six head-to-heads — to flag whether a favorite is robust (wins across the board, like Wood + Estes) or fragile (its lead hinges on a couple of coin-flips). In this short format most favorites are fragile, another reason we never overpay for one team.

5The live auction strategy

Knowing fair values is half the game. The other half is behavior in the room.

The economics — really get this part

$2,500
Buy-team bankroll
5–7
Target teams, $800–1,200 each (hammer)
½
We buy back half of every team we win
$2,000
Hard cap per team — top teams self-buy out of our market
The half-buyback changes everything. By gentleman's agreement, a team can buy back up to half from whoever wins it. We expect to give back half of every team we win. Win a team for $1,000 → hand half back, collect $500 → effective cost $500 for a 50% stake. Read every hammer price as half to us — and every payout as half too. (Win a $6,000 flight? Our 50% share is $3,000 on a $500 effective outlay.)

So our 5–7 targets at $800–1,200 hammer cost only ~$400–600 of real money each after the buyback — fitting a $2,500 bankroll with reserve to spare. And the $2,000 cap helps us: the very best teams get self-bought at the cap, removing them from our market. The exploitable value lives in the strong-but-not-elite middle — exactly where we shop.

6What the tool does live

The numbers here are the prep. On auction night a live tool updates as teams sell:

Bottom line: it keeps us disciplined and adaptive, so we're never bidding on gut feel mid-room.

7Honest limitations

We're confident in this approach, but we won't oversell it: