NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Andrew Novak 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-andrew-novak-win page.
▲ YES EDGE · +0.059 · f★ 6.5% · deploy 3.3% · net 5.17pp
§1 · Position economics
YES · Expected P/L per share +0.0592@ model P(YES) = 0.152
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 6.52% · g(f★) = 1.772%deploy 3.26% · g = 1.391%
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 @ 0.093 · EV +$519stake $815 · 3.26% of bankroll
Deployed stakestake
$815
3.26% of bankroll
Sharesunits
8,766
each pays $1 if YES
Max payoutwin
$8,766
gross, if win
Max profitwin
+$7,951
net of cost
Max losslose
-$815
binary settles to $0
Payout multiple×
×10.75
$1 → $10.75
Risk:RewardR:R
9.75 : 1
win $9.75 per $1
Expected P/LE[P/L]
+$519
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 15.2% | +$7,951 | +$1,210 |
| Resolves against (lose) | 84.8% | -$815 | -$691 |
| Expected value | 100.0% | — | +$519 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +5.9 pprelative edge +63.6%
Required win ratebreak-even
9.3%
price = implied probability
Model win rateP(win)
15.2%
what you forecast
Cushionedge
+5.9 pp
margin of safety
Fair pricemodel
0.152
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
9.3%
= price
Decimal oddsEU
10.753
total return per $1
AmericanUS
+975
$100 wins $975
FractionalUK
9.75 / 1
profit per $1 risked
Profit per $100stake
+$975.27
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 1106% · APY 519913%ROI 63.6% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+63.6%
APR (simple)scaled
+1106%
ROI × 365/days
APY (compounded)if redeployed
+519913%
(1+ROI)^(365/d) − 1
Daily expectedper day
+2.37%
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 +5.17 pperosion 13% · break-even w/ fees 10.1%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$1,630
6.52% · g = 1.772%
Half Kelly½ f★
$815
3.26% · g = 1.391%
Quarter Kelly¼ f★
$408
1.63% · g = 0.852%
Flat 1%1%
$250
1.00% · g = 0.564%
Flat 2%2%
$500
2.00% · g = 0.998%
Flat 5%5%
$1,250
5.00% · g = 1.694%
Recommended¼ f★
$408
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.446 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.615 bit
Δ +0.169 bit vs market
Surprise · YES−log₂ p
3.43 bit
self-information
Surprise · NO−log₂(1−p)
0.14 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0177 nat (0.0256 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 0.152 · CI [0.06, 0.29] · κ 34.8
Posterior meanE[θ]
0.152
Beta(5.3, 29.5)
95% credible intervalHDI
[0.06, 0.29]
price INSIDE → weak edge
Concentrationκ
34.8
pseudo-obs behind belief
Disagreementvs crowd
+5.9 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] +53.2% · P(YES) 14.2% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+53.23%
P(YES) empiricalq
14.2%
Best pathmax
+975.3%
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 1.33% · ruin rate 11.0%400 paths × 120 bets · f deploy 3.26%
Sharpe / betμ/σ
0.162
μ 2.04% · σ 12.6%
Sortino / betμ/σ↓
0.625
downside-only denominator
VaR 95%5%
-3.3%
per-bet worst-case
CVaR 95%ES
-3.3%
mean tail loss
Max drawdownMDD
-20.7%
Calmar 0.06
Ruin rate≤50%
11.0%
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 -31.7pp · crowd gap -37.6pp
Anchor gapmodel − base
-31.7 pp
Crowd gapprice − base
-37.6 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 17.3% · AUC 0.753out-of-sample BSS (5-fold) 17.7% ± 4.1% · Brier 0.2066 · log-loss 0.6195 · n 1600✓ n = 1600
BrierBS
0.2066
lower = better · ō 0.49
BSSvs base
17.3%
improvement over base rate
ReliabilityREL
0.0055
miscalibration · want ↓
ResolutionRES
0.0480
decisiveness · want ↑
Log lossLL
0.6195
cross-entropy
AUCROC
0.753
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)
BLEEDING · PF 0.83 · expectancy -0.097R180 trades · win 44.4% · Sharpe -0.082
Total P/Lnet
-$4,370
on $45,000 cycled
Win ratehit %
44.4%
80 W / 100 L
Profit factorPF
0.83
$ won / $ lost
Expectancyper trade
-$24.28
avg $ per position
R-expectancyper risk
-0.097R
in units of risk taken
Avg win / losspayoff
$257.88 / -$250.00
ratio 1.03 : 1
Sharpe / traderisk-adj
-0.082
μR / σR
Closing line valueCLV
+3.05 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.