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 · +0.032 · f★ 3.2% · deploy 1.6% · net 2.41pp
§1 · Position economics
YES · Expected P/L per share +0.0316@ model P(YES) = 0.048
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 3.22% · g(f★) = 2.043%deploy 1.61% · g = 1.694%
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 @ 0.017 · EV +$772stake $402 · 1.61% of bankroll
Deployed stakestake
$402
1.61% of bankroll
Sharesunits
24,379
each pays $1 if YES
Max payoutwin
$24,379
gross, if win
Max profitwin
+$23,977
net of cost
Max losslose
-$402
binary settles to $0
Payout multiple×
×60.61
$1 → $60.61
Risk:RewardR:R
59.61 : 1
win $59.61 per $1
Expected P/LE[P/L]
+$772
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 4.8% | +$23,977 | +$1,154 |
| Resolves against (lose) | 95.2% | -$402 | -$383 |
| Expected value | 100.0% | — | +$772 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +3.2 pprelative edge +191.8%
Required win ratebreak-even
1.7%
price = implied probability
Model win rateP(win)
4.8%
what you forecast
Cushionedge
+3.2 pp
margin of safety
Fair pricemodel
0.048
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
1.7%
= price
Decimal oddsEU
60.606
total return per $1
AmericanUS
+5961
$100 wins $5961
FractionalUK
59.61 / 1
profit per $1 risked
Profit per $100stake
+$5960.61
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 3334% · APY 12134982972%ROI 191.8% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+191.8%
APR (simple)scaled
+3334%
ROI × 365/days
APY (compounded)if redeployed
+12134982972%
(1+ROI)^(365/d) − 1
Daily expectedper day
+5.23%
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 +2.41 pperosion 24% · 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★
$805
3.22% · g = 2.043%
Half Kelly½ f★
$402
1.61% · g = 1.694%
Quarter Kelly¼ f★
$201
0.80% · g = 1.117%
Flat 1%1%
$250
1.00% · g = 1.295%
Flat 2%2%
$500
2.00% · g = 1.856%
Flat 5%5%
$1,250
5.00% · g = 1.769%
Recommended¼ f★
$201
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.121 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.278 bit
Δ +0.157 bit vs market
Surprise · YES−log₂ p
5.92 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) = 0.0204 nat (0.0295 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 0.048 · CI [0.00, 0.22] · κ 11.7
Posterior meanE[θ]
0.048
Beta(0.6, 11.2)
95% credible intervalHDI
[0.00, 0.22]
price INSIDE → weak edge
Concentrationκ
11.7
pseudo-obs behind belief
Disagreementvs crowd
+2.8 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] +339.4% · P(YES) 7.2% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+339.39%
P(YES) empiricalq
7.2%
Best pathmax
+5960.6%
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 2.42% · ruin rate 8.5%400 paths × 120 bets · f deploy 1.61%
Sharpe / betμ/σ
0.177
μ 4.03% · σ 22.8%
Sortino / betμ/σ↓
2.504
downside-only denominator
VaR 95%5%
-1.6%
per-bet worst-case
CVaR 95%ES
-1.6%
mean tail loss
Max drawdownMDD
-24.1%
Calmar 0.10
Ruin rate≤50%
8.5%
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 -40.4pp · crowd gap -43.5pp
Anchor gapmodel − base
-40.4 pp
Crowd gapprice − base
-43.5 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.