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:
90% of each flight's money stays inside that flight. The owner of the flight winner gets 70% of that flight's pot; the runner-up gets 30%.
10% of the total event pot is skimmed to fund a separate shootout among flight winners.
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 tier
Pot (each)
Winner
Runner-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:
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.
Adds the shared swings — a hard or easy weather day lifts the whole flight; partners in the same group move together.
Plays all five matches hole by hole, applies handicap strokes correctly, and tallies points.
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.
Tier 1 · Most trusted
Jason's human knowledge
Decades of inside read on these members — known sandbaggers, who folds under pressure, who's quietly a different golfer. The model can't see any of it. Examples driving our 2026 board:
Williford (Barbaree + Williford, Fl 8): model rates them a weak 12% "trap" off his ~17 index — but Nick watched Williford shoot 73 in a four-club tournament (near-scratch, hiding 8–9 phantom strokes). The model is simply wrong on a stale number. Human read overrides: a real threat, not the bottom.
Copeland (Wright + Copeland, Fl 5): known sandbagger — and they won Flight 5 in 2025. Buy, with a caveat: he's a hothead, expect volatility.
Fades: the Doyle teams (price inflated off a 2025 Doyle win) and Gallagher + Hansell (let Jason have it; we'd rather own Wood + Estes in Flight 9).
Tier 2 · Hard evidence
Prior-year results (2021–2025)
What teams actually did — five years of finishes the model can't capture. Several 2026 targets already won their flight last year, which validates our direction:
Wood + Estes — won their flight in 2025 (our #1 target).
Downey + Shearer — won their flight in 2025.
Gelinas + Chafin — won their flight in 2025.
Wright + Copeland — won Flight 5 in 2025 (confirms the Copeland sandbag).
Nodar + Heslep and Kessler + Brinson — 2025 runners-up, and model bargains this year too.
A team that's both a model bargain and a recent proven winner is our highest-conviction buy.
Tier 3 · The workhorse
Our simulation
The 40,000-run model from Section 3 — the source of every fair-value number. Trustworthy and unbiased, but it only knows the data (handicaps + posted scores). It anchors the board; the two human layers above correct it where they know better.
Tier 4 · Cross-check only
The Cap Patrol form/clutch algorithm
A third-party tool scoring each player on recent form ("hot right now?") and clutch ("performs under pressure?"). We use it strictly as a cross-check — it's "just an algo," and form especially tends to regress. Its best use is confirmation: it independently flagged Vola + Kerns (our Flight 1 favorite) as over-performing their handicap — nice corroboration. But if it disagrees with Jason or a result, we go with the human and the result.
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.
Buy where the money pools. 90% of value is local to each flight, and low-numbered flights build the biggest pots — so we concentrate there. A few thin "no bueno" flights don't pay enough to bother (even a hot target in a small pot is low-priority). We fade those.
One team per flight. Two teams in the same flight cannibalize each other (only one can win) and waste capital. One shot per flight — our best value in it.
Fade the cheap longshots. The crowd loves a cheap Cinderella; in a Calcutta those are usually the worst value. Solid favorites and strong middles are the sweet spot. We buy value, not upsets.
Hold a reserve. With random auction order, bargains appear anytime — especially late, when rivals run out of cash and prices sag. We keep ~20–25% of bankroll in reserve to pounce.
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:
Tracks all 20 flight pots in real time (plus the grand total) — a team's value depends on how much money its flight is pulling, which is only known once teams start selling.
Re-prices every unsold team after every sale, comparing live fair value to the current bid, and surfaces the best remaining values.
Sets a walk-away max price per team and flags "pounce" moments — when a team sells below fair value and we have reserve to grab it.
Tracks our spend and reserve so we don't overspend early or finish with idle cash.
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:
It's a model, and golf is variance. A 43% favorite still loses its flight more than half the time. Our edge is buying lots of good value, not certainty on any one team. Some of our best buys will whiff — that's normal and already priced in.
The format is genuinely random. 9-hole net better-ball is near-coin-flip; most favorites are "fragile." We lean into that by spreading bets and never overpaying.
The model only knows the data. It can't see sandbaggers or chokers on its own — which is exactly why the human layers sit above it.
The pot projections are estimates. We have no real 2026 prices yet, so pots are projected from 2025 (adjusted for the bigger field and higher cap). The live tool corrects these as real prices come in.
We ignore the shootout on purpose. Small slice, crapshoot. Not worth distorting our bids.