NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Darryn Peterson be the first pick in the 2026 NBA draft?
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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-will-darryn-peterson-be-the-first-pick-in-the-2026-nba-draft page.
▲ YES EDGE · +0.008 · f★ 1.1% · deploy 0.5% · net 0.05pp
§1 · Position economics
YES · Expected P/L per share +0.0080@ model P(YES) = 0.253
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 1.06% · g(f★) = 0.017%deploy 0.53% · g = 0.013%
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 @ 0.245 · EV +$4stake $132 · 0.53% of bankroll
Deployed stakestake
$132
0.53% of bankroll
Sharesunits
540
each pays $1 if YES
Max payoutwin
$540
gross, if win
Max profitwin
+$408
net of cost
Max losslose
-$132
binary settles to $0
Payout multiple×
×4.08
$1 → $4.08
Risk:RewardR:R
3.08 : 1
win $3.08 per $1
Expected P/LE[P/L]
+$4
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 25.3% | +$408 | +$103 |
| Resolves against (lose) | 74.7% | -$132 | -$99 |
| Expected value | 100.0% | — | +$4 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +0.8 pprelative edge +3.3%
Required win ratebreak-even
24.5%
price = implied probability
Model win rateP(win)
25.3%
what you forecast
Cushionedge
+0.8 pp
margin of safety
Fair pricemodel
0.253
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
24.5%
= price
Decimal oddsEU
4.082
total return per $1
AmericanUS
+308
$100 wins $308
FractionalUK
3.08 / 1
profit per $1 risked
Profit per $100stake
+$308.16
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 57% · APY 75%ROI 3.3% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+3.3%
APR (simple)scaled
+57%
ROI × 365/days
APY (compounded)if redeployed
+75%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.15%
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 +0.05 pperosion 94% · break-even w/ fees 25.3%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$265
1.06% · g = 0.017%
Half Kelly½ f★
$132
0.53% · g = 0.013%
Quarter Kelly¼ f★
$66
0.26% · g = 0.008%
Flat 1%1%
$250
1.00% · g = 0.017%
Flat 2%2%
$500
2.00% · g = 0.004%
Flat 5%5%
$1,250
5.00% · g = -0.206%
Recommended¼ f★
$66
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.803 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.816 bit
Δ +0.013 bit vs market
Surprise · YES−log₂ p
2.03 bit
self-information
Surprise · NO−log₂(1−p)
0.41 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0002 nat (0.0002 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 0.253 · CI [0.15, 0.38] · κ 51.5
Posterior meanE[θ]
0.253
Beta(13.0, 38.5)
95% credible intervalHDI
[0.15, 0.38]
price INSIDE → weak edge
Concentrationκ
51.5
pseudo-obs behind belief
Disagreementvs crowd
+0.8 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] +5.1% · P(YES) 25.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+5.10%
P(YES) empiricalq
25.8%
Best pathmax
+308.2%
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 0.01% · ruin rate 0.0%400 paths × 120 bets · f deploy 0.53%
Sharpe / betμ/σ
0.026
μ 0.02% · σ 0.9%
Sortino / betμ/σ↓
0.046
downside-only denominator
VaR 95%5%
-0.5%
per-bet worst-case
CVaR 95%ES
-0.5%
mean tail loss
Max drawdownMDD
-2.1%
Calmar 0.00
Ruin rate≤50%
0.0%
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 -32.5pp
Anchor gapmodel − base
-31.7 pp
Crowd gapprice − base
-32.5 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 19.4% · AUC 0.761out-of-sample BSS (5-fold) 19.4% ± 1.5% · Brier 0.2016 · log-loss 0.6013 · n 1600✓ n = 1600
BrierBS
0.2016
lower = better · ō 0.50
BSSvs base
19.4%
improvement over base rate
ReliabilityREL
0.0044
miscalibration · want ↓
ResolutionRES
0.0519
decisiveness · want ↑
Log lossLL
0.6013
cross-entropy
AUCROC
0.761
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 1.13 · expectancy +0.060R180 trades · win 52.2% · Sharpe 0.052
Total P/Lnet
+$2,706
on $45,000 cycled
Win ratehit %
52.2%
94 W / 86 L
Profit factorPF
1.13
$ won / $ lost
Expectancyper trade
+$15.04
avg $ per position
R-expectancyper risk
+0.060R
in units of risk taken
Avg win / losspayoff
$257.51 / -$250.00
ratio 1.03 : 1
Sharpe / traderisk-adj
0.052
μR / σR
Closing line valueCLV
+2.53 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.