NOSTRADAMUS · Position Analytics Engine

SIMULATOR Will Germany score over 2.5 goals?

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/kalshi-kxwcteamtotal-26jun14gercuw-ger3 page.

▲ YES EDGE · +0.007 · f★ 3.1% · deploy 1.6% · net -0.10pp

§1 · Position economics

Payoff diagram · binary contract P/L vs resolution
YES · Expected P/L per share +0.0065@ model P(YES) = 0.797
-1.00-0.50+0.00+0.50+1.000.000.200.400.600.801.00price 0.790model 0.797YES resolution priceP/L per $1 contract
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
Kelly growth curve · g(f) with f★ and deployed f markers
f★ = 3.12% · g(f★) = 0.013%deploy 1.56% · g = 0.010%
-2.04%-1.53%-1.01%-0.50%0.01%0%8%16%24%32%40%f★ optimumdeployfraction of bankroll fexpected log-growth g(f)
g(f)f★ optimumdeployed fgrowth zone
Underbet leaves growth on the table; overbet destroys capital. The interior maximum is f★.

§2 · The trade ticket

Trade ticket · dollar outcomes at this stake
YES @ 0.790 · EV +$3stake $390 · 1.56% of bankroll
Deployed stakestake
$390
1.56% of bankroll
Sharesunits
493
each pays $1 if YES
Max payoutwin
$493
gross, if win
Max profitwin
+$104
net of cost
Max losslose
-$390
binary settles to $0
Payout multiple×
×1.27
$1 → $1.27
Risk:RewardR:R
0.27 : 1
win $0.27 per $1
Expected P/LE[P/L]
+$3
probability-weighted
OutcomeP(model)P/LContribution
Resolves YES (win)79.7%+$104+$83
Resolves against (lose)20.3%-$390-$79
Expected value100.0%+$3
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.

§3 · Break-even & cushion

Break-even & cushion · margin of safety
Cushion +0.7 pprelative edge +0.8%
Required win ratebreak-even
79.0%
price = implied probability
Model win rateP(win)
79.7%
what you forecast
Cushionedge
+0.7 pp
margin of safety
Fair pricemodel
0.797
where you think it should trade
-60-3003060020406080100you @ 79.0%market price (%)cushion (pp)
The market price equals the win rate you must beat to make money.

§4 · Odds conversion

Implied probability, decimal, American, fractional
Implied probabilityP
79.0%
= price
Decimal oddsEU
1.266
total return per $1
AmericanUS
-376
risk $376 to win $100
FractionalUK
0.27 / 1
profit per $1 risked
Profit per $100stake
+$26.58
clean dollar framing
-1000-5000+500+1000020406080100you · 79.0%implied probability (%)American odds
underdog (+)favorite (-)your price
Five views of the same number.

§4b · Time & annualized return

Time & APR · capital lockup vs annualized return
APR 14% · APY 15%ROI 0.8% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+0.8%
APR (simple)scaled
+14%
ROI × 365/days
APY (compounded)if redeployed
+15%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.04%
geometric, per day held
Capital turns/yrvelocity
×17.4
how often this slot recycles
0%67%133%200%266%333%121416180100120now 21ddays to resolutionannualized return (capped 1000%)
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

Cost waterfall · gross edge → net of friction
Net edge -0.10 pperosion 115% · break-even w/ fees 79.8%
-0.2pp0.0pp0.2pp0.5pp0.7pp0.9pp+0.65Gross edge-0.75- ½ spread+0.00- entry fee+0.00- exit fee-0.10Net edgeEV / share (pp)
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.

§6 · Sizing menu

Sizing menu · disciplined deployment
Full Kellyf★
$780
3.12% · g = 0.013%
Half Kelly½ f★
$390
1.56% · g = 0.010%
Quarter Kelly¼ f★
$195
0.78% · g = 0.006%
Flat 1%1%
$250
1.00% · g = 0.007%
Flat 2%2%
$500
2.00% · g = 0.011%
Flat 5%5%
$1,250
5.00% · g = 0.008%
Recommended¼ f★
$195
survives model error
$0$369$738$1,106$1,475$780Full Kelly3.12%$390Half Kelly1.56%$195Quarter Kelly0.78%$250Flat 1%1.00%$500Flat 2%2.00%$1,250Flat 5%5.00%
Quarter-Kelly is the industry default — survives model error far better than full Kelly.

§7 · Information theory

Binary entropy · uncertainty in bits
Market entropyH(p)
0.741 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.729 bit
Δ -0.013 bit vs market
Surprise · YES−log₂ p
0.34 bit
self-information
Surprise · NO−log₂(1−p)
2.25 bit
self-information
0.000.260.530.791.050.00.20.40.60.81.0marketmodelprobabilityH (bits)
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
KL divergence · upper bound on exploitable edge
NOISE · D_KL(q ‖ p) = 0.0001 nat (0.0002 bit)belief ≈ market — stand down
-0.009-0.004-0.0000.0040.0090.0066YES branch-0.0064NO branchΣKL = 0.0001 natKL contribution (nat)
YES contributionNO contributionbelief ‖ marketnoise
Zero KL ⇒ you know nothing the crowd doesn't.

§8 · Bayesian inference

Bayesian posterior · prior + evidence → belief with 95% CI
MARKET PRICE INSIDE 95% CIposterior μ 0.797 · CI [0.67, 0.90] · κ 44.0
Posterior meanE[θ]
0.797
Beta(35.1, 9.0)
95% credible intervalHDI
[0.67, 0.90]
price INSIDE → weak edge
Concentrationκ
44.0
pseudo-obs behind belief
Disagreementvs crowd
+0.7 pp
posterior − price
0.000.200.400.600.801.00marketposterior μprobability θposterior density
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)

Mark-to-market MC · single position held to resolution
E[P/L] -0.3% · P(YES) 78.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
-0.32%
P(YES) empiricalq
78.8%
Best pathmax
+26.6%
Worst pathmin
-100.0%
VaR 95%5%
100.0%
CVaR 95%ES
100.0%
25¢50¢75¢100¢084168252336420504entry 79.0¢model q 79.7¢bars until resolutionprice path
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)

Monte-Carlo equity fan · this profile, repeated 400× independently
Median CAGR/bet 0.02% · ruin rate 0.0%400 paths × 120 bets · f deploy 1.56%
Sharpe / betμ/σ
0.020
μ 0.02% · σ 0.8%
Sortino / betμ/σ↓
0.010
downside-only denominator
VaR 95%5%
-1.6%
per-bet worst-case
CVaR 95%ES
-1.6%
mean tail loss
Max drawdownMDD
-2.0%
Calmar 0.01
Ruin rate≤50%
0.0%
P(equity ever ≤ 50%)
0.83×0.91×0.99×1.07×1.15×1.23×020406080100120startruin 50%bet #bankroll multiple
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

Probability stack · base rate vs crowd vs model
ANCHORED · supported by convictionanchor gap +21.3pp · crowd gap +20.6pp
0%20%40%60%80%100%Reference base rate58.4%Market price79.0%Model P(YES)79.7%
Anchor gapmodel − base
+21.3 pp
Crowd gapprice − base
+20.6 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.

§11 · Forecast quality (synthetic ledger)

Brier · Murphy decomposition · reliability · ROC
SKILL POSITIVE · in-sample BSS 19.3% · AUC 0.764out-of-sample BSS (5-fold) 19.5% ± 2.5% · Brier 0.2015 · log-loss 0.6069 · n 1600n = 1600
BrierBS
0.2015
lower = better · ō 0.49
BSSvs base
19.3%
improvement over base rate
ReliabilityREL
0.0061
miscalibration · want ↓
ResolutionRES
0.0537
decisiveness · want ↑
Log lossLL
0.6069
cross-entropy
AUCROC
0.764
0.5 coin · 1.0 oracle
0.00.20.40.60.81.00.00.20.40.60.81.0stated probability fobserved frequency ō0.00.20.40.60.81.00.00.20.40.60.81.0AUC = 0.764false positive ratetrue positive rate0.0000.0750.1500.2250.3000.250UNC0.054RES0.006REL0.202BRIERcontribution
calibration curveROCUNC (irreducible)RES (skill, ↑)REL (miscalib, ↓)
Computed on a seeded synthetic forecast ledger. Reseed (⟳) to redraw.

§12 · Journal vitals (synthetic ledger)

Track record · win rate · PF · expectancy · CLV · equity curve
PROFITABLE · PF 1.16 · expectancy +0.077R180 trades · win 53.3% · Sharpe 0.065
Total P/Lnet
+$3,448
on $45,000 cycled
Win ratehit %
53.3%
96 W / 84 L
Profit factorPF
1.16
$ won / $ lost
Expectancyper trade
+$19.15
avg $ per position
R-expectancyper risk
+0.077R
in units of risk taken
Avg win / losspayoff
$254.66 / -$250.00
ratio 1.02 : 1
Sharpe / traderisk-adj
0.065
μR / σR
Closing line valueCLV
+3.01 pp
avg edge vs close
-$1,211$179$1,569$2,959$4,34903672108144180trade #cumulative P/L (USD)
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.

▸ Advanced metrics · M2M bundle

kalshi · kxwcteamtotal-26jun14gercuw-ger3 · fresh · feed 21s old
24h sparkline · 60 pts 11.27%
realized vol (ann.)
305.83%
max drawdown
6.17%
sharpe
ulcer index
2.30%
RMS drawdown
pain index
1.70%
mean drawdown
mod. VaR 95%
0.55%
Cornish-Fisher
martin ratio
ret / ulcer
CDaR 95%
4.24%
cond. drawdown
gain/pain
1.14
Σgain / Σ|loss|
sterling
ret / CDaR
omega (θ=0)
1.14
upside/downside
roll spread
43.8 bps
implied (price-only)
bars used
766
store
spread
127.4 bps
24h Δ
11.27%
flow lean
carry
flat
signalNEUTRALconfidence 25%
  • 24h change +11.27%
Same bundle via M2M API: /api/m2m/kalshi-kxwcteamtotal-26jun14gercuw-ger3/bundle · venue execution: kalshi