NOSTRADAMUS · Position Analytics Engine
SIMULATOR Exact Score: Netherlands 2 - 3 Japan?
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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-fifwc-nld-jpn-2026-06-14-exact-score-2-3 page.
▲ YES EDGE · +0.019 · f★ 2.0% · deploy 1.0% · net 1.19pp
§1 · Position economics
YES · Expected P/L per share +0.0194@ model P(YES) = 0.037
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 1.97% · g(f★) = 0.829%deploy 0.99% · g = 0.669%
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 @ 0.018 · EV +$272stake $246 · 0.99% of bankroll
Deployed stakestake
$246
0.99% of bankroll
Sharesunits
14,072
each pays $1 if YES
Max payoutwin
$14,072
gross, if win
Max profitwin
+$13,826
net of cost
Max losslose
-$246
binary settles to $0
Payout multiple×
×57.14
$1 → $57.14
Risk:RewardR:R
56.14 : 1
win $56.14 per $1
Expected P/LE[P/L]
+$272
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 3.7% | +$13,826 | +$510 |
| Resolves against (lose) | 96.3% | -$246 | -$237 |
| Expected value | 100.0% | — | +$272 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +1.9 pprelative edge +110.6%
Required win ratebreak-even
1.8%
price = implied probability
Model win rateP(win)
3.7%
what you forecast
Cushionedge
+1.9 pp
margin of safety
Fair pricemodel
0.037
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
1.8%
= price
Decimal oddsEU
57.143
total return per $1
AmericanUS
+5614
$100 wins $5614
FractionalUK
56.14 / 1
profit per $1 risked
Profit per $100stake
+$5614.29
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 1922% · APY 41899385%ROI 110.6% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+110.6%
APR (simple)scaled
+1922%
ROI × 365/days
APY (compounded)if redeployed
+41899385%
(1+ROI)^(365/d) − 1
Daily expectedper day
+3.61%
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 +1.19 pperosion 39% · break-even w/ fees 2.5%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$493
1.97% · g = 0.829%
Half Kelly½ f★
$246
0.99% · g = 0.669%
Quarter Kelly¼ f★
$123
0.49% · g = 0.424%
Flat 1%1%
$250
1.00% · g = 0.674%
Flat 2%2%
$500
2.00% · g = 0.829%
Flat 5%5%
$1,250
5.00% · g = -0.013%
Recommended¼ f★
$123
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.127 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.228 bit
Δ +0.101 bit vs market
Surprise · YES−log₂ p
5.84 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) = 0.0083 nat (0.0120 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 0.037 · CI [0.00, 0.22] · κ 8.9
Posterior meanE[θ]
0.037
Beta(0.3, 8.5)
95% credible intervalHDI
[0.00, 0.22]
price INSIDE → weak edge
Concentrationκ
8.9
pseudo-obs behind belief
Disagreementvs crowd
+1.7 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] +142.9% · P(YES) 4.3% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+142.86%
P(YES) empiricalq
4.3%
Best pathmax
+5614.3%
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 1.27% · ruin rate 4.0%400 paths × 120 bets · f deploy 0.99%
Sharpe / betμ/σ
0.146
μ 1.78% · σ 12.2%
Sortino / betμ/σ↓
1.806
downside-only denominator
VaR 95%5%
-1.0%
per-bet worst-case
CVaR 95%ES
-1.0%
mean tail loss
Max drawdownMDD
-18.8%
Calmar 0.07
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 -49.4pp · crowd gap -51.4pp
Anchor gapmodel − base
-49.4 pp
Crowd gapprice − base
-51.4 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 19.9% · AUC 0.766out-of-sample BSS (5-fold) 20.0% ± 3.4% · Brier 0.2002 · log-loss 0.5982 · n 1600✓ n = 1600
BrierBS
0.2002
lower = better · ō 0.50
BSSvs base
19.9%
improvement over base rate
ReliabilityREL
0.0050
miscalibration · want ↓
ResolutionRES
0.0551
decisiveness · want ↑
Log lossLL
0.5982
cross-entropy
AUCROC
0.766
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 1.20 · expectancy +0.086R180 trades · win 56.1% · Sharpe 0.079
Total P/Lnet
+$3,888
on $45,000 cycled
Win ratehit %
56.1%
101 W / 79 L
Profit factorPF
1.20
$ won / $ lost
Expectancyper trade
+$21.60
avg $ per position
R-expectancyper risk
+0.086R
in units of risk taken
Avg win / losspayoff
$234.04 / -$250.00
ratio 0.94 : 1
Sharpe / traderisk-adj
0.079
μR / σR
Closing line valueCLV
+2.24 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.