NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will G2 win IEM Cologne Major 2026?
← Back to live dashboardEmbed cardOG previewTop moversArb
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-g2-win-iem-cologne-major-2026 page.
▲ YES EDGE · +0.018 · f★ 1.8% · deploy 0.9% · net 1.03pp
§1 · Position economics
YES · Expected P/L per share +0.0178@ model P(YES) = 0.032
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 1.81% · g(f★) = 0.849%deploy 0.90% · g = 0.690%
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 @ 0.014 · EV +$288stake $226 · 0.90% of bankroll
Deployed stakestake
$226
0.90% of bankroll
Sharesunits
16,158
each pays $1 if YES
Max payoutwin
$16,158
gross, if win
Max profitwin
+$15,932
net of cost
Max losslose
-$226
binary settles to $0
Payout multiple×
×71.43
$1 → $71.43
Risk:RewardR:R
70.43 : 1
win $70.43 per $1
Expected P/LE[P/L]
+$288
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 3.2% | +$15,932 | +$507 |
| Resolves against (lose) | 96.8% | -$226 | -$219 |
| Expected value | 100.0% | — | +$288 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +1.8 pprelative edge +127.5%
Required win ratebreak-even
1.4%
price = implied probability
Model win rateP(win)
3.2%
what you forecast
Cushionedge
+1.8 pp
margin of safety
Fair pricemodel
0.032
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
1.4%
= price
Decimal oddsEU
71.429
total return per $1
AmericanUS
+7043
$100 wins $7043
FractionalUK
70.43 / 1
profit per $1 risked
Profit per $100stake
+$7042.86
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 2215% · APY 159689817%ROI 127.5% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+127.5%
APR (simple)scaled
+2215%
ROI × 365/days
APY (compounded)if redeployed
+159689817%
(1+ROI)^(365/d) − 1
Daily expectedper day
+3.99%
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 +1.03 pperosion 42% · break-even w/ fees 2.1%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$452
1.81% · g = 0.849%
Half Kelly½ f★
$226
0.90% · g = 0.690%
Quarter Kelly¼ f★
$113
0.45% · g = 0.442%
Flat 1%1%
$250
1.00% · g = 0.725%
Flat 2%2%
$500
2.00% · g = 0.843%
Flat 5%5%
$1,250
5.00% · g = -0.161%
Recommended¼ f★
$113
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.106 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.204 bit
Δ +0.097 bit vs market
Surprise · YES−log₂ p
6.16 bit
self-information
Surprise · NO−log₂(1−p)
0.02 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0085 nat (0.0122 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 0.032 · CI [0.00, 0.23] · κ 7.6
Posterior meanE[θ]
0.032
Beta(0.2, 7.3)
95% credible intervalHDI
[0.00, 0.23]
price INSIDE → weak edge
Concentrationκ
7.6
pseudo-obs behind belief
Disagreementvs crowd
+1.2 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] +78.6% · P(YES) 2.5% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+78.57%
P(YES) empiricalq
2.5%
Best pathmax
+7042.9%
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 1.43% · ruin rate 3.5%400 paths × 120 bets · f deploy 0.90%
Sharpe / betμ/σ
0.154
μ 2.09% · σ 13.6%
Sortino / betμ/σ↓
2.307
downside-only denominator
VaR 95%5%
-0.9%
per-bet worst-case
CVaR 95%ES
-0.9%
mean tail loss
Max drawdownMDD
-16.6%
Calmar 0.09
Ruin rate≤50%
3.5%
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 -50.4pp · crowd gap -52.2pp
Anchor gapmodel − base
-50.4 pp
Crowd gapprice − base
-52.2 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 19.5% · AUC 0.764out-of-sample BSS (5-fold) 19.6% ± 2.0% · Brier 0.2013 · log-loss 0.5983 · n 1600✓ n = 1600
BrierBS
0.2013
lower = better · ō 0.49
BSSvs base
19.5%
improvement over base rate
ReliabilityREL
0.0046
miscalibration · want ↓
ResolutionRES
0.0536
decisiveness · want ↑
Log lossLL
0.5983
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 0.82 · expectancy -0.098R180 trades · win 46.7% · Sharpe -0.094
Total P/Lnet
-$4,411
on $45,000 cycled
Win ratehit %
46.7%
84 W / 96 L
Profit factorPF
0.82
$ won / $ lost
Expectancyper trade
-$24.50
avg $ per position
R-expectancyper risk
-0.098R
in units of risk taken
Avg win / losspayoff
$233.21 / -$250.00
ratio 0.93 : 1
Sharpe / traderisk-adj
-0.094
μR / σR
Closing line valueCLV
+2.64 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.