NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Aurora 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-aurora-win-iem-cologne-major-2026 page.
▲ YES EDGE · +0.039 · f★ 4.0% · deploy 2.0% · net 3.14pp
§1 · Position economics
YES · Expected P/L per share +0.0389@ model P(YES) = 0.068
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 4.00% · g(f★) = 1.937%deploy 2.00% · g = 1.574%
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 @ 0.029 · EV +$659stake $500 · 2.00% of bankroll
Deployed stakestake
$500
2.00% of bankroll
Sharesunits
16,963
each pays $1 if YES
Max payoutwin
$16,963
gross, if win
Max profitwin
+$16,462
net of cost
Max losslose
-$500
binary settles to $0
Payout multiple×
×33.90
$1 → $33.90
Risk:RewardR:R
32.90 : 1
win $32.90 per $1
Expected P/LE[P/L]
+$659
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 6.8% | +$16,462 | +$1,125 |
| Resolves against (lose) | 93.2% | -$500 | -$466 |
| Expected value | 100.0% | — | +$659 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +3.9 pprelative edge +131.7%
Required win ratebreak-even
2.9%
price = implied probability
Model win rateP(win)
6.8%
what you forecast
Cushionedge
+3.9 pp
margin of safety
Fair pricemodel
0.068
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
2.9%
= price
Decimal oddsEU
33.898
total return per $1
AmericanUS
+3290
$100 wins $3290
FractionalUK
32.90 / 1
profit per $1 risked
Profit per $100stake
+$3289.83
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 2289% · APY 220151618%ROI 131.7% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+131.7%
APR (simple)scaled
+2289%
ROI × 365/days
APY (compounded)if redeployed
+220151618%
(1+ROI)^(365/d) − 1
Daily expectedper day
+4.08%
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 +3.14 pperosion 19% · break-even w/ fees 3.7%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$1,001
4.00% · g = 1.937%
Half Kelly½ f★
$500
2.00% · g = 1.574%
Quarter Kelly¼ f★
$250
1.00% · g = 1.008%
Flat 1%1%
$250
1.00% · g = 1.008%
Flat 2%2%
$500
2.00% · g = 1.574%
Flat 5%5%
$1,250
5.00% · g = 1.869%
Recommended¼ f★
$250
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.192 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.360 bit
Δ +0.168 bit vs market
Surprise · YES−log₂ p
5.08 bit
self-information
Surprise · NO−log₂(1−p)
0.04 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0194 nat (0.0279 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 0.068 · CI [0.00, 0.22] · κ 16.7
Posterior meanE[θ]
0.068
Beta(1.1, 15.5)
95% credible intervalHDI
[0.00, 0.22]
price INSIDE → weak edge
Concentrationκ
16.7
pseudo-obs behind belief
Disagreementvs crowd
+3.9 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] +137.3% · P(YES) 7.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+137.29%
P(YES) empiricalq
7.0%
Best pathmax
+3289.8%
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 1.94% · ruin rate 11.0%400 paths × 120 bets · f deploy 2.00%
Sharpe / betμ/σ
0.171
μ 3.04% · σ 17.8%
Sortino / betμ/σ↓
1.520
downside-only denominator
VaR 95%5%
-2.0%
per-bet worst-case
CVaR 95%ES
-2.0%
mean tail loss
Max drawdownMDD
-26.2%
Calmar 0.07
Ruin rate≤50%
11.0%
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 -45.5pp · crowd gap -49.4pp
Anchor gapmodel − base
-45.5 pp
Crowd gapprice − base
-49.4 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 22.3% · AUC 0.778out-of-sample BSS (5-fold) 22.4% ± 1.9% · Brier 0.1943 · log-loss 0.5822 · n 1600✓ n = 1600
BrierBS
0.1943
lower = better · ō 0.50
BSSvs base
22.3%
improvement over base rate
ReliabilityREL
0.0044
miscalibration · want ↓
ResolutionRES
0.0594
decisiveness · want ↑
Log lossLL
0.5822
cross-entropy
AUCROC
0.778
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 +0.044R180 trades · win 52.2% · Sharpe 0.039
Total P/Lnet
+$1,960
on $45,000 cycled
Win ratehit %
52.2%
94 W / 86 L
Profit factorPF
1.09
$ won / $ lost
Expectancyper trade
+$10.89
avg $ per position
R-expectancyper risk
+0.044R
in units of risk taken
Avg win / losspayoff
$249.58 / -$250.00
ratio 1.00 : 1
Sharpe / traderisk-adj
0.039
μR / σR
Closing line valueCLV
+2.68 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.