NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Morocco win the 2026 FIFA World Cup?
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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-morocco-win-the-2026-fifa-world-cup-464 page.
▲ YES EDGE · +0.015 · f★ 1.5% · deploy 0.8% · net 0.76pp
§1 · Position economics
YES · Expected P/L per share +0.0151@ model P(YES) = 0.038
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 1.55% · g(f★) = 0.433%deploy 0.77% · g = 0.342%
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 @ 0.022 · EV +$130stake $193 · 0.77% of bankroll
Deployed stakestake
$193
0.77% of bankroll
Sharesunits
8,588
each pays $1 if YES
Max payoutwin
$8,588
gross, if win
Max profitwin
+$8,395
net of cost
Max losslose
-$193
binary settles to $0
Payout multiple×
×44.44
$1 → $44.44
Risk:RewardR:R
43.44 : 1
win $43.44 per $1
Expected P/LE[P/L]
+$130
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 3.8% | +$8,395 | +$316 |
| Resolves against (lose) | 96.2% | -$193 | -$186 |
| Expected value | 100.0% | — | +$130 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +1.5 pprelative edge +67.2%
Required win ratebreak-even
2.3%
price = implied probability
Model win rateP(win)
3.8%
what you forecast
Cushionedge
+1.5 pp
margin of safety
Fair pricemodel
0.038
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
2.3%
= price
Decimal oddsEU
44.444
total return per $1
AmericanUS
+4344
$100 wins $4344
FractionalUK
43.44 / 1
profit per $1 risked
Profit per $100stake
+$4344.44
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 1167% · APY 755514%ROI 67.2% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+67.2%
APR (simple)scaled
+1167%
ROI × 365/days
APY (compounded)if redeployed
+755514%
(1+ROI)^(365/d) − 1
Daily expectedper day
+2.48%
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 +0.76 pperosion 50% · break-even w/ fees 3.0%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$386
1.55% · g = 0.433%
Half Kelly½ f★
$193
0.77% · g = 0.342%
Quarter Kelly¼ f★
$97
0.39% · g = 0.211%
Flat 1%1%
$250
1.00% · g = 0.390%
Flat 2%2%
$500
2.00% · g = 0.408%
Flat 5%5%
$1,250
5.00% · g = -0.594%
Recommended¼ f★
$97
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.155 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.231 bit
Δ +0.076 bit vs market
Surprise · YES−log₂ p
5.47 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) = 0.0043 nat (0.0062 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 0.038 · CI [0.00, 0.22] · κ 9.1
Posterior meanE[θ]
0.038
Beta(0.3, 8.7)
95% credible intervalHDI
[0.00, 0.22]
price INSIDE → weak edge
Concentrationκ
9.1
pseudo-obs behind belief
Disagreementvs crowd
+1.5 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] +111.1% · P(YES) 4.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+111.11%
P(YES) empiricalq
4.8%
Best pathmax
+4344.4%
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 0.60% · ruin rate 0.5%400 paths × 120 bets · f deploy 0.77%
Sharpe / betμ/σ
0.118
μ 0.87% · σ 7.3%
Sortino / betμ/σ↓
1.119
downside-only denominator
VaR 95%5%
-0.8%
per-bet worst-case
CVaR 95%ES
-0.8%
mean tail loss
Max drawdownMDD
-15.0%
Calmar 0.04
Ruin rate≤50%
0.5%
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 -56.1pp · crowd gap -57.6pp
Anchor gapmodel − base
-56.1 pp
Crowd gapprice − base
-57.6 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 14.9% · AUC 0.740out-of-sample BSS (5-fold) 15.0% ± 1.2% · Brier 0.2128 · log-loss 0.6324 · n 1600✓ n = 1600
BrierBS
0.2128
lower = better · ō 0.51
BSSvs base
14.9%
improvement over base rate
ReliabilityREL
0.0072
miscalibration · want ↓
ResolutionRES
0.0446
decisiveness · want ↑
Log lossLL
0.6324
cross-entropy
AUCROC
0.740
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 1.06 · expectancy +0.031R180 trades · win 52.2% · Sharpe 0.028
Total P/Lnet
+$1,390
on $45,000 cycled
Win ratehit %
52.2%
94 W / 86 L
Profit factorPF
1.06
$ won / $ lost
Expectancyper trade
+$7.72
avg $ per position
R-expectancyper risk
+0.031R
in units of risk taken
Avg win / losspayoff
$243.51 / -$250.00
ratio 0.97 : 1
Sharpe / traderisk-adj
0.028
μR / σR
Closing line valueCLV
+2.84 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.