NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Patrick Reed 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-patrick-reed-win page.
▲ YES EDGE · +0.022 · f★ 2.3% · deploy 1.1% · net 1.48pp
§1 · Position economics
YES · Expected P/L per share +0.0223@ model P(YES) = 0.046
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 2.28% · g(f★) = 0.852%deploy 1.14% · g = 0.683%
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 @ 0.024 · EV +$271stake $286 · 1.14% of bankroll
Deployed stakestake
$286
1.14% of bankroll
Sharesunits
12,150
each pays $1 if YES
Max payoutwin
$12,150
gross, if win
Max profitwin
+$11,864
net of cost
Max losslose
-$286
binary settles to $0
Payout multiple×
×42.55
$1 → $42.55
Risk:RewardR:R
41.55 : 1
win $41.55 per $1
Expected P/LE[P/L]
+$271
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 4.6% | +$11,864 | +$543 |
| Resolves against (lose) | 95.4% | -$286 | -$272 |
| Expected value | 100.0% | — | +$271 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +2.2 pprelative edge +94.9%
Required win ratebreak-even
2.4%
price = implied probability
Model win rateP(win)
4.6%
what you forecast
Cushionedge
+2.2 pp
margin of safety
Fair pricemodel
0.046
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
2.4%
= price
Decimal oddsEU
42.553
total return per $1
AmericanUS
+4155
$100 wins $4155
FractionalUK
41.55 / 1
profit per $1 risked
Profit per $100stake
+$4155.32
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 1650% · APY 10908569%ROI 94.9% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+94.9%
APR (simple)scaled
+1650%
ROI × 365/days
APY (compounded)if redeployed
+10908569%
(1+ROI)^(365/d) − 1
Daily expectedper day
+3.23%
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 +1.48 pperosion 34% · break-even w/ fees 3.1%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$571
2.28% · g = 0.852%
Half Kelly½ f★
$286
1.14% · g = 0.683%
Quarter Kelly¼ f★
$143
0.57% · g = 0.429%
Flat 1%1%
$250
1.00% · g = 0.633%
Flat 2%2%
$500
2.00% · g = 0.843%
Flat 5%5%
$1,250
5.00% · g = 0.255%
Recommended¼ f★
$143
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.161 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.268 bit
Δ +0.108 bit vs market
Surprise · YES−log₂ p
5.41 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) = 0.0085 nat (0.0123 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 0.046 · CI [0.00, 0.22] · κ 11.1
Posterior meanE[θ]
0.046
Beta(0.5, 10.6)
95% credible intervalHDI
[0.00, 0.22]
price INSIDE → weak edge
Concentrationκ
11.1
pseudo-obs behind belief
Disagreementvs crowd
+2.2 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] +123.4% · P(YES) 5.3% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+123.40%
P(YES) empiricalq
5.3%
Best pathmax
+4155.3%
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 0.85% · ruin rate 3.3%400 paths × 120 bets · f deploy 1.14%
Sharpe / betμ/σ
0.141
μ 1.58% · σ 11.2%
Sortino / betμ/σ↓
1.383
downside-only denominator
VaR 95%5%
-1.1%
per-bet worst-case
CVaR 95%ES
-1.1%
mean tail loss
Max drawdownMDD
-19.6%
Calmar 0.04
Ruin rate≤50%
3.3%
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 -46.9pp · crowd gap -49.1pp
Anchor gapmodel − base
-46.9 pp
Crowd gapprice − base
-49.1 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 22.9% · AUC 0.783out-of-sample BSS (5-fold) 22.9% ± 1.9% · Brier 0.1926 · log-loss 0.5744 · n 1600✓ n = 1600
BrierBS
0.1926
lower = better · ō 0.51
BSSvs base
22.9%
improvement over base rate
ReliabilityREL
0.0038
miscalibration · want ↓
ResolutionRES
0.0606
decisiveness · want ↑
Log lossLL
0.5744
cross-entropy
AUCROC
0.783
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 1.02 · expectancy +0.010R180 trades · win 49.4% · Sharpe 0.007
Total P/Lnet
+$433
on $45,000 cycled
Win ratehit %
49.4%
89 W / 91 L
Profit factorPF
1.02
$ won / $ lost
Expectancyper trade
+$2.40
avg $ per position
R-expectancyper risk
+0.010R
in units of risk taken
Avg win / losspayoff
$260.48 / -$250.00
ratio 1.04 : 1
Sharpe / traderisk-adj
0.007
μR / σR
Closing line valueCLV
+2.38 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.