NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Australia 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-australia-win-the-2026-fifa-world-cup-816 page.
▲ YES EDGE · +0.017 · f★ 1.7% · deploy 0.9% · net 0.96pp
§1 · Position economics
YES · Expected P/L per share +0.0171@ model P(YES) = 0.021
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 1.72% · g(f★) = 1.958%deploy 0.86% · g = 1.705%
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 @ 0.004 · EV +$1,049stake $215 · 0.86% of bankroll
Deployed stakestake
$215
0.86% of bankroll
Sharesunits
61,329
each pays $1 if YES
Max payoutwin
$61,329
gross, if win
Max profitwin
+$61,114
net of cost
Max losslose
-$215
binary settles to $0
Payout multiple×
×285.71
$1 → $285.71
Risk:RewardR:R
284.71 : 1
win $284.71 per $1
Expected P/LE[P/L]
+$1,049
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 2.1% | +$61,114 | +$1,260 |
| Resolves against (lose) | 97.9% | -$215 | -$210 |
| Expected value | 100.0% | — | +$1,049 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +1.7 pprelative edge +488.9%
Required win ratebreak-even
0.4%
price = implied probability
Model win rateP(win)
2.1%
what you forecast
Cushionedge
+1.7 pp
margin of safety
Fair pricemodel
0.021
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
0.4%
= price
Decimal oddsEU
285.714
total return per $1
AmericanUS
+28471
$100 wins $28471
FractionalUK
284.71 / 1
profit per $1 risked
Profit per $100stake
+$28471.43
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 8498% · APY 2422350080518487%ROI 488.9% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+488.9%
APR (simple)scaled
+8498%
ROI × 365/days
APY (compounded)if redeployed
+2422350080518487%
(1+ROI)^(365/d) − 1
Daily expectedper day
+8.81%
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 +0.96 pperosion 44% · break-even w/ fees 1.1%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$429
1.72% · g = 1.958%
Half Kelly½ f★
$215
0.86% · g = 1.705%
Quarter Kelly¼ f★
$107
0.43% · g = 1.225%
Flat 1%1%
$250
1.00% · g = 1.793%
Flat 2%2%
$500
2.00% · g = 1.940%
Flat 5%5%
$1,250
5.00% · g = 0.590%
Recommended¼ f★
$107
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.034 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.145 bit
Δ +0.111 bit vs market
Surprise · YES−log₂ p
8.16 bit
self-information
Surprise · NO−log₂(1−p)
0.01 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0196 nat (0.0283 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 0.021 · CI [0.00, 0.29] · κ 4.6
Posterior meanE[θ]
0.021
Beta(0.1, 4.5)
95% credible intervalHDI
[0.00, 0.29]
price INSIDE → weak edge
Concentrationκ
4.6
pseudo-obs behind belief
Disagreementvs crowd
+0.1 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] +614.3% · P(YES) 2.5% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+614.29%
P(YES) empiricalq
2.5%
Best pathmax
+28471.4%
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 4.42% · ruin rate 4.0%400 paths × 120 bets · f deploy 0.86%
Sharpe / betμ/σ
0.188
μ 9.06% · σ 48.3%
Sortino / betμ/σ↓
10.554
downside-only denominator
VaR 95%5%
-0.9%
per-bet worst-case
CVaR 95%ES
-0.9%
mean tail loss
Max drawdownMDD
-19.4%
Calmar 0.23
Ruin rate≤50%
4.0%
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 -38.9pp · crowd gap -40.6pp
Anchor gapmodel − base
-38.9 pp
Crowd gapprice − base
-40.6 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 19.8% · AUC 0.764out-of-sample BSS (5-fold) 20.0% ± 2.4% · Brier 0.2004 · log-loss 0.5935 · n 1600✓ n = 1600
BrierBS
0.2004
lower = better · ō 0.51
BSSvs base
19.8%
improvement over base rate
ReliabilityREL
0.0046
miscalibration · want ↓
ResolutionRES
0.0539
decisiveness · want ↑
Log lossLL
0.5935
cross-entropy
AUCROC
0.764
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 0.86 · expectancy -0.070R180 trades · win 48.9% · Sharpe -0.068
Total P/Lnet
-$3,128
on $45,000 cycled
Win ratehit %
48.9%
88 W / 92 L
Profit factorPF
0.86
$ won / $ lost
Expectancyper trade
-$17.38
avg $ per position
R-expectancyper risk
-0.070R
in units of risk taken
Avg win / losspayoff
$225.81 / -$250.00
ratio 0.90 : 1
Sharpe / traderisk-adj
-0.068
μR / σR
Closing line valueCLV
+3.31 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.