NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will USA 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-usa-win-the-2026-fifa-world-cup-467 page.
▲ YES EDGE · +0.005 · f★ 0.5% · deploy 0.3% · net -0.22pp
§1 · Position economics
YES · Expected P/L per share +0.0053@ model P(YES) = 0.026
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 0.54% · g(f★) = 0.065%deploy 0.27% · g = 0.050%
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 @ 0.021 · EV +$18stake $68 · 0.27% of bankroll
Deployed stakestake
$68
0.27% of bankroll
Sharesunits
3,311
each pays $1 if YES
Max payoutwin
$3,311
gross, if win
Max profitwin
+$3,243
net of cost
Max losslose
-$68
binary settles to $0
Payout multiple×
×48.78
$1 → $48.78
Risk:RewardR:R
47.78 : 1
win $47.78 per $1
Expected P/LE[P/L]
+$18
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 2.6% | +$3,243 | +$84 |
| Resolves against (lose) | 97.4% | -$68 | -$66 |
| Expected value | 100.0% | — | +$18 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +0.5 pprelative edge +25.9%
Required win ratebreak-even
2.1%
price = implied probability
Model win rateP(win)
2.6%
what you forecast
Cushionedge
+0.5 pp
margin of safety
Fair pricemodel
0.026
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
2.1%
= price
Decimal oddsEU
48.780
total return per $1
AmericanUS
+4778
$100 wins $4778
FractionalUK
47.78 / 1
profit per $1 risked
Profit per $100stake
+$4778.05
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 451% · APY 5413%ROI 25.9% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+25.9%
APR (simple)scaled
+451%
ROI × 365/days
APY (compounded)if redeployed
+5413%
(1+ROI)^(365/d) − 1
Daily expectedper day
+1.10%
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 -0.22 pperosion 141% · break-even w/ fees 2.8%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$136
0.54% · g = 0.065%
Half Kelly½ f★
$68
0.27% · g = 0.050%
Quarter Kelly¼ f★
$34
0.14% · g = 0.030%
Flat 1%1%
$250
1.00% · g = 0.029%
Flat 2%2%
$500
2.00% · g = -0.236%
Flat 5%5%
$1,250
5.00% · g = -1.846%
Recommended¼ f★
$34
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.144 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.173 bit
Δ +0.029 bit vs market
Surprise · YES−log₂ p
5.61 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) = 0.0007 nat (0.0009 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 0.026 · CI [0.00, 0.26] · κ 6.0
Posterior meanE[θ]
0.026
Beta(0.2, 5.8)
95% credible intervalHDI
[0.00, 0.26]
price INSIDE → weak edge
Concentrationκ
6.0
pseudo-obs behind belief
Disagreementvs crowd
+0.5 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] +34.1% · P(YES) 2.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+34.15%
P(YES) empiricalq
2.8%
Best pathmax
+4778.0%
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 0.41% · ruin rate 0.0%400 paths × 120 bets · f deploy 0.50%
Sharpe / betμ/σ
0.109
μ 0.53% · σ 4.9%
Sortino / betμ/σ↓
1.068
downside-only denominator
VaR 95%5%
-0.5%
per-bet worst-case
CVaR 95%ES
-0.5%
mean tail loss
Max drawdownMDD
-11.3%
Calmar 0.04
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 -55.5pp · crowd gap -56.0pp
Anchor gapmodel − base
-55.5 pp
Crowd gapprice − base
-56.0 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 18.6% · AUC 0.759out-of-sample BSS (5-fold) 18.7% ± 2.0% · Brier 0.2026 · log-loss 0.6028 · n 1600✓ n = 1600
BrierBS
0.2026
lower = better · ō 0.53
BSSvs base
18.6%
improvement over base rate
ReliabilityREL
0.0051
miscalibration · want ↓
ResolutionRES
0.0516
decisiveness · want ↑
Log lossLL
0.6028
cross-entropy
AUCROC
0.759
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 0.87 · expectancy -0.069R180 trades · win 48.3% · Sharpe -0.065
Total P/Lnet
-$3,089
on $45,000 cycled
Win ratehit %
48.3%
87 W / 93 L
Profit factorPF
0.87
$ won / $ lost
Expectancyper trade
-$17.16
avg $ per position
R-expectancyper risk
-0.069R
in units of risk taken
Avg win / losspayoff
$231.74 / -$250.00
ratio 0.93 : 1
Sharpe / traderisk-adj
-0.065
μR / σR
Closing line valueCLV
+2.25 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.