NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Jason Day 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-jason-day-win page.
▲ YES EDGE · +0.051 · f★ 5.2% · deploy 2.6% · net 4.37pp
§1 · Position economics
YES · Expected P/L per share +0.0512@ model P(YES) = 0.060
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 5.16% · g(f★) = 6.646%deploy 2.58% · g = 5.829%
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 @ 0.009 · EV +$3,884stake $645 · 2.58% of bankroll
Deployed stakestake
$645
2.58% of bankroll
Sharesunits
75,900
each pays $1 if YES
Max payoutwin
$75,900
gross, if win
Max profitwin
+$75,255
net of cost
Max losslose
-$645
binary settles to $0
Payout multiple×
×117.65
$1 → $117.65
Risk:RewardR:R
116.65 : 1
win $116.65 per $1
Expected P/LE[P/L]
+$3,884
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 6.0% | +$75,255 | +$4,491 |
| Resolves against (lose) | 94.0% | -$645 | -$607 |
| Expected value | 100.0% | — | +$3,884 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +5.1 pprelative edge +602.0%
Required win ratebreak-even
0.9%
price = implied probability
Model win rateP(win)
6.0%
what you forecast
Cushionedge
+5.1 pp
margin of safety
Fair pricemodel
0.060
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
0.9%
= price
Decimal oddsEU
117.647
total return per $1
AmericanUS
+11665
$100 wins $11665
FractionalUK
116.65 / 1
profit per $1 risked
Profit per $100stake
+$11664.71
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 10464% · APY 51355579814072136%ROI 602.0% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+602.0%
APR (simple)scaled
+10464%
ROI × 365/days
APY (compounded)if redeployed
+51355579814072136%
(1+ROI)^(365/d) − 1
Daily expectedper day
+9.72%
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 +4.37 pperosion 15% · break-even w/ fees 1.6%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$1,290
5.16% · g = 6.646%
Half Kelly½ f★
$645
2.58% · g = 5.829%
Quarter Kelly¼ f★
$323
1.29% · g = 4.259%
Flat 1%1%
$250
1.00% · g = 3.668%
Flat 2%2%
$500
2.00% · g = 5.284%
Flat 5%5%
$1,250
5.00% · g = 6.644%
Recommended¼ f★
$323
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.071 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.326 bit
Δ +0.255 bit vs market
Surprise · YES−log₂ p
6.88 bit
self-information
Surprise · NO−log₂(1−p)
0.01 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
SIGNAL · D_KL(q ‖ p) = 0.0665 nat (0.0959 bit)exploitable edge present
YES contributionNO contributionbelief ‖ marketsignal
Zero KL ⇒ you know nothing the crowd doesn't.
§8 · Bayesian inference
MARKET PRICE INSIDE 95% CIposterior μ 0.060 · CI [0.00, 0.22] · κ 14.6
Posterior meanE[θ]
0.060
Beta(0.9, 13.7)
95% credible intervalHDI
[0.00, 0.22]
price INSIDE → weak edge
Concentrationκ
14.6
pseudo-obs behind belief
Disagreementvs crowd
+4.0 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] +458.8% · P(YES) 4.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+458.82%
P(YES) empiricalq
4.8%
Best pathmax
+11664.7%
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 7.06% · ruin rate 17.0%400 paths × 120 bets · f deploy 2.58%
Sharpe / betμ/σ
0.227
μ 16.93% · σ 74.5%
Sortino / betμ/σ↓
6.561
downside-only denominator
VaR 95%5%
-2.6%
per-bet worst-case
CVaR 95%ES
-2.6%
mean tail loss
Max drawdownMDD
-34.2%
Calmar 0.21
Ruin rate≤50%
17.0%
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 -38.2pp · crowd gap -43.4pp
Anchor gapmodel − base
-38.2 pp
Crowd gapprice − base
-43.4 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 17.2% · AUC 0.753out-of-sample BSS (5-fold) 17.3% ± 2.7% · Brier 0.2064 · log-loss 0.6141 · n 1600✓ n = 1600
BrierBS
0.2064
lower = better · ō 0.47
BSSvs base
17.2%
improvement over base rate
ReliabilityREL
0.0059
miscalibration · want ↓
ResolutionRES
0.0488
decisiveness · want ↑
Log lossLL
0.6141
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)
PROFITABLE · PF 1.28 · expectancy +0.126R180 trades · win 55.6% · Sharpe 0.114
Total P/Lnet
+$5,668
on $45,000 cycled
Win ratehit %
55.6%
100 W / 80 L
Profit factorPF
1.28
$ won / $ lost
Expectancyper trade
+$31.49
avg $ per position
R-expectancyper risk
+0.126R
in units of risk taken
Avg win / losspayoff
$256.68 / -$250.00
ratio 1.03 : 1
Sharpe / traderisk-adj
0.114
μR / σR
Closing line valueCLV
+2.99 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.