NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Natus Vincere win IEM Cologne Major 2026?
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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-natus-vincere-win-iem-cologne-major-2026 page.
▲ YES EDGE · +0.010 · f★ 1.1% · deploy 0.5% · net 0.24pp
§1 · Position economics
YES · Expected P/L per share +0.0099@ model P(YES) = 0.084
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 1.07% · g(f★) = 0.068%deploy 0.53% · g = 0.052%
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 @ 0.074 · EV +$18stake $133 · 0.53% of bankroll
Deployed stakestake
$133
0.53% of bankroll
Sharesunits
1,801
each pays $1 if YES
Max payoutwin
$1,801
gross, if win
Max profitwin
+$1,668
net of cost
Max losslose
-$133
binary settles to $0
Payout multiple×
×13.51
$1 → $13.51
Risk:RewardR:R
12.51 : 1
win $12.51 per $1
Expected P/LE[P/L]
+$18
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 8.4% | +$1,668 | +$140 |
| Resolves against (lose) | 91.6% | -$133 | -$122 |
| 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 +1.0 pprelative edge +13.3%
Required win ratebreak-even
7.4%
price = implied probability
Model win rateP(win)
8.4%
what you forecast
Cushionedge
+1.0 pp
margin of safety
Fair pricemodel
0.084
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
7.4%
= price
Decimal oddsEU
13.514
total return per $1
AmericanUS
+1251
$100 wins $1251
FractionalUK
12.51 / 1
profit per $1 risked
Profit per $100stake
+$1251.35
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 232% · APY 782%ROI 13.3% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+13.3%
APR (simple)scaled
+232%
ROI × 365/days
APY (compounded)if redeployed
+782%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.60%
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 8.1%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$267
1.07% · g = 0.068%
Half Kelly½ f★
$133
0.53% · g = 0.052%
Quarter Kelly¼ f★
$67
0.27% · g = 0.031%
Flat 1%1%
$250
1.00% · g = 0.068%
Flat 2%2%
$500
2.00% · g = 0.023%
Flat 5%5%
$1,250
5.00% · g = -0.624%
Recommended¼ f★
$67
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.381 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.416 bit
Δ +0.035 bit vs market
Surprise · YES−log₂ p
3.76 bit
self-information
Surprise · NO−log₂(1−p)
0.11 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0007 nat (0.0010 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 0.084 · CI [0.01, 0.23] · κ 20.3
Posterior meanE[θ]
0.084
Beta(1.7, 18.6)
95% credible intervalHDI
[0.01, 0.23]
price INSIDE → weak edge
Concentrationκ
20.3
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] -22.3% · P(YES) 5.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
-22.30%
P(YES) empiricalq
5.8%
Best pathmax
+1251.4%
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 0.05% · ruin rate 0.0%400 paths × 120 bets · f deploy 0.53%
Sharpe / betμ/σ
0.047
μ 0.09% · σ 2.0%
Sortino / betμ/σ↓
0.177
downside-only denominator
VaR 95%5%
-0.5%
per-bet worst-case
CVaR 95%ES
-0.5%
mean tail loss
Max drawdownMDD
-7.2%
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 -45.9pp · crowd gap -46.9pp
Anchor gapmodel − base
-45.9 pp
Crowd gapprice − base
-46.9 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 23.4% · AUC 0.784out-of-sample BSS (5-fold) 23.5% ± 0.8% · Brier 0.1911 · log-loss 0.5742 · n 1600✓ n = 1600
BrierBS
0.1911
lower = better · ō 0.52
BSSvs base
23.4%
improvement over base rate
ReliabilityREL
0.0031
miscalibration · want ↓
ResolutionRES
0.0622
decisiveness · want ↑
Log lossLL
0.5742
cross-entropy
AUCROC
0.784
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 1.23 · expectancy +0.108R180 trades · win 53.3% · Sharpe 0.092
Total P/Lnet
+$4,874
on $45,000 cycled
Win ratehit %
53.3%
96 W / 84 L
Profit factorPF
1.23
$ won / $ lost
Expectancyper trade
+$27.08
avg $ per position
R-expectancyper risk
+0.108R
in units of risk taken
Avg win / losspayoff
$269.52 / -$250.00
ratio 1.08 : 1
Sharpe / traderisk-adj
0.092
μR / σR
Closing line valueCLV
+3.25 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.