NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will England win Group L in 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-england-win-group-l-in-the-2026-fifa-world-cup page.
▲ YES EDGE · +0.016 · f★ 18.4% · deploy 9.2% · net 0.81pp
§1 · Position economics
YES · Expected P/L per share +0.0156@ model P(YES) = 0.931
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 18.36% · g(f★) = 0.166%deploy 9.18% · g = 0.122%
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 @ 0.915 · EV +$39stake $2,295 · 9.18% of bankroll
Deployed stakestake
$2,295
9.18% of bankroll
Sharesunits
2,508
each pays $1 if YES
Max payoutwin
$2,508
gross, if win
Max profitwin
+$213
net of cost
Max losslose
-$2,295
binary settles to $0
Payout multiple×
×1.09
$1 → $1.09
Risk:RewardR:R
0.09 : 1
win $0.09 per $1
Expected P/LE[P/L]
+$39
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 93.1% | +$213 | +$198 |
| Resolves against (lose) | 6.9% | -$2,295 | -$159 |
| Expected value | 100.0% | — | +$39 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +1.6 pprelative edge +1.7%
Required win ratebreak-even
91.5%
price = implied probability
Model win rateP(win)
93.1%
what you forecast
Cushionedge
+1.6 pp
margin of safety
Fair pricemodel
0.931
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
91.5%
= price
Decimal oddsEU
1.093
total return per $1
AmericanUS
-1076
risk $1076 to win $100
FractionalUK
0.09 / 1
profit per $1 risked
Profit per $100stake
+$9.29
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 30% · APY 34%ROI 1.7% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+1.7%
APR (simple)scaled
+30%
ROI × 365/days
APY (compounded)if redeployed
+34%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.08%
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 +0.81 pperosion 48% · break-even w/ fees 92.3%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$4,590
18.36% · g = 0.166%
Half Kelly½ f★
$2,295
9.18% · g = 0.122%
Quarter Kelly¼ f★
$1,148
4.59% · g = 0.070%
Flat 1%1%
$250
1.00% · g = 0.017%
Flat 2%2%
$500
2.00% · g = 0.033%
Flat 5%5%
$1,250
5.00% · g = 0.075%
Recommended¼ f★
$1,148
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.420 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.364 bit
Δ -0.056 bit vs market
Surprise · YES−log₂ p
0.13 bit
self-information
Surprise · NO−log₂(1−p)
3.56 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0017 nat (0.0024 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 0.931 · CI [0.77, 1.00] · κ 16.9
Posterior meanE[θ]
0.931
Beta(15.8, 1.2)
95% credible intervalHDI
[0.77, 1.00]
price INSIDE → weak edge
Concentrationκ
16.9
pseudo-obs behind belief
Disagreementvs crowd
+1.6 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] +1.6% · P(YES) 93.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+1.64%
P(YES) empiricalq
93.0%
Best pathmax
+9.3%
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 0.06% · ruin rate 1.0%400 paths × 120 bets · f deploy 9.18%
Sharpe / betμ/σ
0.043
μ 0.11% · σ 2.6%
Sortino / betμ/σ↓
0.012
downside-only denominator
VaR 95%5%
-9.2%
per-bet worst-case
CVaR 95%ES
-9.2%
mean tail loss
Max drawdownMDD
-9.2%
Calmar 0.01
Ruin rate≤50%
1.0%
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 +41.7pp · crowd gap +40.1pp
Anchor gapmodel − base
+41.7 pp
Crowd gapprice − base
+40.1 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 17.5% · AUC 0.752out-of-sample BSS (5-fold) 17.7% ± 3.6% · Brier 0.2063 · log-loss 0.6126 · n 1600✓ n = 1600
BrierBS
0.2063
lower = better · ō 0.50
BSSvs base
17.5%
improvement over base rate
ReliabilityREL
0.0053
miscalibration · want ↓
ResolutionRES
0.0488
decisiveness · want ↑
Log lossLL
0.6126
cross-entropy
AUCROC
0.752
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 1.09 · expectancy +0.041R180 trades · win 53.9% · Sharpe 0.038
Total P/Lnet
+$1,827
on $45,000 cycled
Win ratehit %
53.9%
97 W / 83 L
Profit factorPF
1.09
$ won / $ lost
Expectancyper trade
+$10.15
avg $ per position
R-expectancyper risk
+0.041R
in units of risk taken
Avg win / losspayoff
$232.75 / -$250.00
ratio 0.93 : 1
Sharpe / traderisk-adj
0.038
μR / σR
Closing line valueCLV
+3.14 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.