NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Sam Burns win the 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/kalshi-kxpgatour-uso26-sbur page.
▲ YES EDGE · +0.033 · f★ 3.4% · deploy 1.7% · net 2.52pp
§1 · Position economics
YES · Expected P/L per share +0.0327@ model P(YES) = 0.064
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 3.37% · g(f★) = 1.370%deploy 1.68% · g = 1.102%
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 @ 0.031 · EV +$444stake $421 · 1.68% of bankroll
Deployed stakestake
$421
1.68% of bankroll
Sharesunits
13,587
each pays $1 if YES
Max payoutwin
$13,587
gross, if win
Max profitwin
+$13,166
net of cost
Max losslose
-$421
binary settles to $0
Payout multiple×
×32.26
$1 → $32.26
Risk:RewardR:R
31.26 : 1
win $31.26 per $1
Expected P/LE[P/L]
+$444
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 6.4% | +$13,166 | +$838 |
| Resolves against (lose) | 93.6% | -$421 | -$394 |
| Expected value | 100.0% | — | +$444 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +3.3 pprelative edge +105.3%
Required win ratebreak-even
3.1%
price = implied probability
Model win rateP(win)
6.4%
what you forecast
Cushionedge
+3.3 pp
margin of safety
Fair pricemodel
0.064
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
3.1%
= price
Decimal oddsEU
32.258
total return per $1
AmericanUS
+3126
$100 wins $3126
FractionalUK
31.26 / 1
profit per $1 risked
Profit per $100stake
+$3125.81
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 1831% · APY 26947894%ROI 105.3% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+105.3%
APR (simple)scaled
+1831%
ROI × 365/days
APY (compounded)if redeployed
+26947894%
(1+ROI)^(365/d) − 1
Daily expectedper day
+3.49%
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 +2.52 pperosion 23% · break-even w/ fees 3.9%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$842
3.37% · g = 1.370%
Half Kelly½ f★
$421
1.68% · g = 1.102%
Quarter Kelly¼ f★
$211
0.84% · g = 0.696%
Flat 1%1%
$250
1.00% · g = 0.790%
Flat 2%2%
$500
2.00% · g = 1.199%
Flat 5%5%
$1,250
5.00% · g = 1.188%
Recommended¼ f★
$211
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.199 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.342 bit
Δ +0.142 bit vs market
Surprise · YES−log₂ p
5.01 bit
self-information
Surprise · NO−log₂(1−p)
0.05 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0137 nat (0.0198 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 0.064 · CI [0.00, 0.22] · κ 15.6
Posterior meanE[θ]
0.064
Beta(1.0, 14.6)
95% credible intervalHDI
[0.00, 0.22]
price INSIDE → weak edge
Concentrationκ
15.6
pseudo-obs behind belief
Disagreementvs crowd
+3.3 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] +85.5% · P(YES) 5.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+85.48%
P(YES) empiricalq
5.8%
Best pathmax
+3125.8%
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 1.24% · ruin rate 9.3%400 paths × 120 bets · f deploy 1.68%
Sharpe / betμ/σ
0.151
μ 2.08% · σ 13.8%
Sortino / betμ/σ↓
1.236
downside-only denominator
VaR 95%5%
-1.7%
per-bet worst-case
CVaR 95%ES
-1.7%
mean tail loss
Max drawdownMDD
-27.6%
Calmar 0.05
Ruin rate≤50%
9.3%
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 -44.4pp · crowd gap -47.7pp
Anchor gapmodel − base
-44.4 pp
Crowd gapprice − base
-47.7 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 22.7% · AUC 0.780out-of-sample BSS (5-fold) 22.7% ± 2.8% · Brier 0.1932 · log-loss 0.5803 · n 1600✓ n = 1600
BrierBS
0.1932
lower = better · ō 0.51
BSSvs base
22.7%
improvement over base rate
ReliabilityREL
0.0026
miscalibration · want ↓
ResolutionRES
0.0596
decisiveness · want ↑
Log lossLL
0.5803
cross-entropy
AUCROC
0.780
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 1.19 · expectancy +0.086R180 trades · win 53.3% · Sharpe 0.077
Total P/Lnet
+$3,885
on $45,000 cycled
Win ratehit %
53.3%
96 W / 84 L
Profit factorPF
1.19
$ won / $ lost
Expectancyper trade
+$21.58
avg $ per position
R-expectancyper risk
+0.086R
in units of risk taken
Avg win / losspayoff
$259.22 / -$250.00
ratio 1.04 : 1
Sharpe / traderisk-adj
0.077
μR / σR
Closing line valueCLV
+2.27 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.