NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Chris Gotterup win the 2026 U.S. Open?
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A live, interactive instrument for dissecting a single binary position. Sweep the inputs and watch every indicator recompute — payoff geometry, Kelly growth, Bayesian posterior, KL divergence, cost waterfall, Monte-Carlo equity fan, forecast calibration. Companion to the live /feed/pm-2026-us-open-winner-chris-gotterup-win page.
▲ YES EDGE · +0.032 · f★ 3.3% · deploy 1.7% · net 2.48pp
§1 · Position economics
YES · Expected P/L per share +0.0323@ model P(YES) = 0.054
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 3.30% · g(f★) = 1.731%deploy 1.65% · g = 1.415%
g(f)f★ optimumdeployed fgrowth zone
Underbet leaves growth on the table; overbet destroys capital. The interior maximum is f★.
§2 · The trade ticket
YES @ 0.022 · EV +$606stake $413 · 1.65% of bankroll
Deployed stakestake
$413
1.65% of bankroll
Sharesunits
18,770
each pays $1 if YES
Max payoutwin
$18,770
gross, if win
Max profitwin
+$18,357
net of cost
Max losslose
-$413
binary settles to $0
Payout multiple×
×45.45
$1 → $45.45
Risk:RewardR:R
44.45 : 1
win $44.45 per $1
Expected P/LE[P/L]
+$606
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 5.4% | +$18,357 | +$997 |
| Resolves against (lose) | 94.6% | -$413 | -$391 |
| Expected value | 100.0% | — | +$606 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +3.2 pprelative edge +146.9%
Required win ratebreak-even
2.2%
price = implied probability
Model win rateP(win)
5.4%
what you forecast
Cushionedge
+3.2 pp
margin of safety
Fair pricemodel
0.054
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
2.2%
= price
Decimal oddsEU
45.455
total return per $1
AmericanUS
+4445
$100 wins $4445
FractionalUK
44.45 / 1
profit per $1 risked
Profit per $100stake
+$4445.45
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 2553% · APY 662457282%ROI 146.9% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+146.9%
APR (simple)scaled
+2553%
ROI × 365/days
APY (compounded)if redeployed
+662457282%
(1+ROI)^(365/d) − 1
Daily expectedper day
+4.40%
geometric, per day held
Capital turns/yrvelocity
×17.4
how often this slot recycles
simple APRcompounded APYyour horizon
Rank positions by APR, not raw ROI. A thin edge tomorrow beats a fat edge next year.
§5 · Costs & net edge
Net edge +2.48 pperosion 23% · break-even w/ fees 2.9%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$826
3.30% · g = 1.731%
Half Kelly½ f★
$413
1.65% · g = 1.415%
Quarter Kelly¼ f★
$206
0.83% · g = 0.914%
Flat 1%1%
$250
1.00% · g = 1.047%
Flat 2%2%
$500
2.00% · g = 1.544%
Flat 5%5%
$1,250
5.00% · g = 1.505%
Recommended¼ f★
$206
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.153 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.304 bit
Δ +0.152 bit vs market
Surprise · YES−log₂ p
5.51 bit
self-information
Surprise · NO−log₂(1−p)
0.03 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0173 nat (0.0250 bit)belief ≈ market — stand down
YES contributionNO contributionbelief ‖ marketnoise
Zero KL ⇒ you know nothing the crowd doesn't.
§8 · Bayesian inference
MARKET PRICE INSIDE 95% CIposterior μ 0.054 · CI [0.00, 0.22] · κ 13.3
Posterior meanE[θ]
0.054
Beta(0.7, 12.5)
95% credible intervalHDI
[0.00, 0.22]
price INSIDE → weak edge
Concentrationκ
13.3
pseudo-obs behind belief
Disagreementvs crowd
+3.2 pp
posterior − price
market prior (dashed)model posterior95% credible bandmarket price
When the market price falls outside the 95% credible interval, your disagreement is statistically meaningful.
§9 · Tail risk · Monte-Carlo (mode A · single position to resolution)
E[P/L] +81.8% · P(YES) 4.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+81.82%
P(YES) empiricalq
4.0%
Best pathmax
+4445.5%
Worst pathmin
-100.0%
VaR 95%5%
100.0%
CVaR 95%ES
100.0%
median path25/75 + 5/95 bandsentry pricemodel q
Logit-space mean-reverting walk + terminal flip with probability q. Answers: 'what happens to THIS one position'. Distinct from the repeated-edge fan below.
§9b · Tail risk · Monte-Carlo (mode B · repeated independent edges)
Median CAGR/bet 2.14% · ruin rate 8.8%400 paths × 120 bets · f deploy 1.65%
Sharpe / betμ/σ
0.171
μ 3.13% · σ 18.3%
Sortino / betμ/σ↓
1.896
downside-only denominator
VaR 95%5%
-1.7%
per-bet worst-case
CVaR 95%ES
-1.7%
mean tail loss
Max drawdownMDD
-24.7%
Calmar 0.09
Ruin rate≤50%
8.8%
P(equity ever ≤ 50%)
median25/75 band5/95 bandruin line
Answers a different question: 'if I could find this exact edge forever, what is the bankroll trajectory'. Compounds 120 sequential resolutions which is NOT what happens to a single position.
§10 · Base-rate & macro context
ANCHORED · supported by convictionanchor gap -39.0pp · crowd gap -42.2pp
Anchor gapmodel − base
-39.0 pp
Crowd gapprice − base
-42.2 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 19.9% · AUC 0.766out-of-sample BSS (5-fold) 20.1% ± 1.1% · Brier 0.2001 · log-loss 0.5997 · n 1600✓ n = 1600
BrierBS
0.2001
lower = better · ō 0.49
BSSvs base
19.9%
improvement over base rate
ReliabilityREL
0.0045
miscalibration · want ↓
ResolutionRES
0.0540
decisiveness · want ↑
Log lossLL
0.5997
cross-entropy
AUCROC
0.766
0.5 coin · 1.0 oracle
calibration curveROCUNC (irreducible)RES (skill, ↑)REL (miscalib, ↓)
Computed on a seeded synthetic forecast ledger. Reseed (⟳) to redraw.
§12 · Journal vitals (synthetic ledger)
PROFITABLE · PF 1.15 · expectancy +0.069R180 trades · win 53.9% · Sharpe 0.063
Total P/Lnet
+$3,115
on $45,000 cycled
Win ratehit %
53.9%
97 W / 83 L
Profit factorPF
1.15
$ won / $ lost
Expectancyper trade
+$17.30
avg $ per position
R-expectancyper risk
+0.069R
in units of risk taken
Avg win / losspayoff
$246.03 / -$250.00
ratio 0.98 : 1
Sharpe / traderisk-adj
0.063
μR / σR
Closing line valueCLV
+2.62 pp
avg edge vs close
cumulative P/Lprofitable zonered zonesynthetic · seeded from asset
The scorecard every trader checks. Synthetic ledger seeded from the asset slug — recomputes against your real fill history once wired.