NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will FUT 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-fut-win-iem-cologne-major-2026 page.
▲ YES EDGE · +0.037 · f★ 3.7% · deploy 1.9% · net 2.90pp
§1 · Position economics
YES · Expected P/L per share +0.0365@ model P(YES) = 0.053
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 3.71% · g(f★) = 2.659%deploy 1.86% · g = 2.224%
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 @ 0.016 · EV +$1,059stake $464 · 1.86% of bankroll
Deployed stakestake
$464
1.86% of bankroll
Sharesunits
28,991
each pays $1 if YES
Max payoutwin
$28,991
gross, if win
Max profitwin
+$28,527
net of cost
Max losslose
-$464
binary settles to $0
Payout multiple×
×62.50
$1 → $62.50
Risk:RewardR:R
61.50 : 1
win $61.50 per $1
Expected P/LE[P/L]
+$1,059
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 5.3% | +$28,527 | +$1,498 |
| Resolves against (lose) | 94.7% | -$464 | -$439 |
| Expected value | 100.0% | — | +$1,059 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +3.7 pprelative edge +228.2%
Required win ratebreak-even
1.6%
price = implied probability
Model win rateP(win)
5.3%
what you forecast
Cushionedge
+3.7 pp
margin of safety
Fair pricemodel
0.053
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
1.6%
= price
Decimal oddsEU
62.500
total return per $1
AmericanUS
+6150
$100 wins $6150
FractionalUK
61.50 / 1
profit per $1 risked
Profit per $100stake
+$6150.00
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 3967% · APY 93627323446%ROI 228.2% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+228.2%
APR (simple)scaled
+3967%
ROI × 365/days
APY (compounded)if redeployed
+93627323446%
(1+ROI)^(365/d) − 1
Daily expectedper day
+5.82%
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 +2.90 pperosion 21% · break-even w/ fees 2.4%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$928
3.71% · g = 2.659%
Half Kelly½ f★
$464
1.86% · g = 2.224%
Quarter Kelly¼ f★
$232
0.93% · g = 1.488%
Flat 1%1%
$250
1.00% · g = 1.565%
Flat 2%2%
$500
2.00% · g = 2.298%
Flat 5%5%
$1,250
5.00% · g = 2.518%
Recommended¼ f★
$232
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.118 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.297 bit
Δ +0.179 bit vs market
Surprise · YES−log₂ p
5.97 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).
SIGNAL · D_KL(q ‖ p) = 0.0266 nat (0.0384 bit)exploitable edge present
YES contributionNO contributionbelief ‖ marketsignal
Zero KL ⇒ you know nothing the crowd doesn't.
§8 · Bayesian inference
MARKET PRICE INSIDE 95% CIposterior μ 0.053 · CI [0.00, 0.22] · κ 12.8
Posterior meanE[θ]
0.053
Beta(0.7, 12.1)
95% credible intervalHDI
[0.00, 0.22]
price INSIDE → weak edge
Concentrationκ
12.8
pseudo-obs behind belief
Disagreementvs crowd
+3.3 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] +400.0% · P(YES) 8.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+400.00%
P(YES) empiricalq
8.0%
Best pathmax
+6150.0%
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 2.71% · ruin rate 10.0%400 paths × 120 bets · f deploy 1.86%
Sharpe / betμ/σ
0.188
μ 5.22% · σ 27.8%
Sortino / betμ/σ↓
2.814
downside-only denominator
VaR 95%5%
-1.9%
per-bet worst-case
CVaR 95%ES
-1.9%
mean tail loss
Max drawdownMDD
-27.3%
Calmar 0.10
Ruin rate≤50%
10.0%
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 -39.9pp · crowd gap -43.6pp
Anchor gapmodel − base
-39.9 pp
Crowd gapprice − base
-43.6 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 20.5% · AUC 0.770out-of-sample BSS (5-fold) 20.6% ± 1.7% · Brier 0.1988 · log-loss 0.5926 · n 1600✓ n = 1600
BrierBS
0.1988
lower = better · ō 0.50
BSSvs base
20.5%
improvement over base rate
ReliabilityREL
0.0042
miscalibration · want ↓
ResolutionRES
0.0558
decisiveness · want ↑
Log lossLL
0.5926
cross-entropy
AUCROC
0.770
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 1.29 · expectancy +0.124R180 trades · win 57.8% · Sharpe 0.111
Total P/Lnet
+$5,588
on $45,000 cycled
Win ratehit %
57.8%
104 W / 76 L
Profit factorPF
1.29
$ won / $ lost
Expectancyper trade
+$31.05
avg $ per position
R-expectancyper risk
+0.124R
in units of risk taken
Avg win / losspayoff
$236.43 / -$250.00
ratio 0.95 : 1
Sharpe / traderisk-adj
0.111
μR / σR
Closing line valueCLV
+2.84 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.