NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Morocco win Group C in the 2026 FIFA World Cup?
← Back to live dashboardEmbed cardOG previewTop moversArb
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-group-c-in-the-2026-fifa-world-cup page.
▲ YES EDGE · +0.010 · f★ 1.4% · deploy 0.7% · net 0.24pp
§1 · Position economics
YES · Expected P/L per share +0.0099@ model P(YES) = 0.305
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 1.40% · g(f★) = 0.023%deploy 0.70% · g = 0.018%
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 @ 0.295 · EV +$6stake $176 · 0.70% of bankroll
Deployed stakestake
$176
0.70% of bankroll
Sharesunits
595
each pays $1 if YES
Max payoutwin
$595
gross, if win
Max profitwin
+$420
net of cost
Max losslose
-$176
binary settles to $0
Payout multiple×
×3.39
$1 → $3.39
Risk:RewardR:R
2.39 : 1
win $2.39 per $1
Expected P/LE[P/L]
+$6
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 30.5% | +$420 | +$128 |
| Resolves against (lose) | 69.5% | -$176 | -$122 |
| Expected value | 100.0% | — | +$6 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +1.0 pprelative edge +3.4%
Required win ratebreak-even
29.5%
price = implied probability
Model win rateP(win)
30.5%
what you forecast
Cushionedge
+1.0 pp
margin of safety
Fair pricemodel
0.305
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
29.5%
= price
Decimal oddsEU
3.390
total return per $1
AmericanUS
+239
$100 wins $239
FractionalUK
2.39 / 1
profit per $1 risked
Profit per $100stake
+$238.98
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 58% · APY 78%ROI 3.4% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+3.4%
APR (simple)scaled
+58%
ROI × 365/days
APY (compounded)if redeployed
+78%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.16%
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 +0.24 pperosion 76% · break-even w/ fees 30.3%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$351
1.40% · g = 0.023%
Half Kelly½ f★
$176
0.70% · g = 0.018%
Quarter Kelly¼ f★
$88
0.35% · g = 0.010%
Flat 1%1%
$250
1.00% · g = 0.021%
Flat 2%2%
$500
2.00% · g = 0.019%
Flat 5%5%
$1,250
5.00% · g = -0.124%
Recommended¼ f★
$88
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.875 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.887 bit
Δ +0.012 bit vs market
Surprise · YES−log₂ p
1.76 bit
self-information
Surprise · NO−log₂(1−p)
0.50 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0002 nat (0.0003 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 0.305 · CI [0.19, 0.43] · κ 57.9
Posterior meanE[θ]
0.305
Beta(17.6, 40.2)
95% credible intervalHDI
[0.19, 0.43]
price INSIDE → weak edge
Concentrationκ
57.9
pseudo-obs behind belief
Disagreementvs crowd
+1.0 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] +18.6% · P(YES) 35.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+18.64%
P(YES) empiricalq
35.0%
Best pathmax
+239.0%
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 0.03% · ruin rate 0.0%400 paths × 120 bets · f deploy 0.70%
Sharpe / betμ/σ
0.023
μ 0.03% · σ 1.1%
Sortino / betμ/σ↓
0.036
downside-only denominator
VaR 95%5%
-0.7%
per-bet worst-case
CVaR 95%ES
-0.7%
mean tail loss
Max drawdownMDD
-2.5%
Calmar 0.01
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 -26.7pp · crowd gap -27.7pp
Anchor gapmodel − base
-26.7 pp
Crowd gapprice − base
-27.7 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 22.1% · AUC 0.780out-of-sample BSS (5-fold) 22.2% ± 4.3% · Brier 0.1941 · log-loss 0.5814 · n 1600✓ n = 1600
BrierBS
0.1941
lower = better · ō 0.47
BSSvs base
22.1%
improvement over base rate
ReliabilityREL
0.0056
miscalibration · want ↓
ResolutionRES
0.0601
decisiveness · want ↑
Log lossLL
0.5814
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)
BLEEDING · PF 0.82 · expectancy -0.090R180 trades · win 48.9% · Sharpe -0.089
Total P/Lnet
-$4,044
on $45,000 cycled
Win ratehit %
48.9%
88 W / 92 L
Profit factorPF
0.82
$ won / $ lost
Expectancyper trade
-$22.47
avg $ per position
R-expectancyper risk
-0.090R
in units of risk taken
Avg win / losspayoff
$215.41 / -$250.00
ratio 0.86 : 1
Sharpe / traderisk-adj
-0.089
μR / σR
Closing line valueCLV
+2.54 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.