NOSTRADAMUS · Position Analytics Engine
SIMULATOR Grass Court Championships, Qualification: Suzan Lamens vs Dalma Galfi
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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-wta-lamens-galfi-2026-06-14 page.
▲ YES EDGE · +0.054 · f★ 18.7% · deploy 9.3% · net 4.66pp
§1 · Position economics
YES · Expected P/L per share +0.0541@ model P(YES) = 0.764
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 18.67% · g(f★) = 0.741%deploy 9.33% · g = 0.548%
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 @ 0.710 · EV +$178stake $2,334 · 9.33% of bankroll
Deployed stakestake
$2,334
9.33% of bankroll
Sharesunits
3,287
each pays $1 if YES
Max payoutwin
$3,287
gross, if win
Max profitwin
+$953
net of cost
Max losslose
-$2,334
binary settles to $0
Payout multiple×
×1.41
$1 → $1.41
Risk:RewardR:R
0.41 : 1
win $0.41 per $1
Expected P/LE[P/L]
+$178
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 76.4% | +$953 | +$728 |
| Resolves against (lose) | 23.6% | -$2,334 | -$550 |
| Expected value | 100.0% | — | +$178 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +5.4 pprelative edge +7.6%
Required win ratebreak-even
71.0%
price = implied probability
Model win rateP(win)
76.4%
what you forecast
Cushionedge
+5.4 pp
margin of safety
Fair pricemodel
0.764
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
71.0%
= price
Decimal oddsEU
1.408
total return per $1
AmericanUS
-245
risk $245 to win $100
FractionalUK
0.41 / 1
profit per $1 risked
Profit per $100stake
+$40.85
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 133% · APY 259%ROI 7.6% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+7.6%
APR (simple)scaled
+133%
ROI × 365/days
APY (compounded)if redeployed
+259%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.35%
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 +4.66 pperosion 14% · break-even w/ fees 71.7%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$4,667
18.67% · g = 0.741%
Half Kelly½ f★
$2,334
9.33% · g = 0.548%
Quarter Kelly¼ f★
$1,167
4.67% · g = 0.316%
Flat 1%1%
$250
1.00% · g = 0.074%
Flat 2%2%
$500
2.00% · g = 0.145%
Flat 5%5%
$1,250
5.00% · g = 0.335%
Recommended¼ f★
$1,167
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.869 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.788 bit
Δ -0.081 bit vs market
Surprise · YES−log₂ p
0.49 bit
self-information
Surprise · NO−log₂(1−p)
1.79 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0074 nat (0.0107 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 0.764 · CI [0.64, 0.87] · κ 49.1
Posterior meanE[θ]
0.764
Beta(37.5, 11.6)
95% credible intervalHDI
[0.64, 0.87]
price INSIDE → weak edge
Concentrationκ
49.1
pseudo-obs behind belief
Disagreementvs crowd
+5.4 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] +7.0% · P(YES) 76.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+7.04%
P(YES) empiricalq
76.0%
Best pathmax
+40.8%
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 0.58% · ruin rate 7.2%400 paths × 120 bets · f deploy 9.33%
Sharpe / betμ/σ
0.129
μ 0.72% · σ 5.6%
Sortino / betμ/σ↓
0.077
downside-only denominator
VaR 95%5%
-9.3%
per-bet worst-case
CVaR 95%ES
-9.3%
mean tail loss
Max drawdownMDD
-9.3%
Calmar 0.06
Ruin rate≤50%
7.2%
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 +17.9pp · crowd gap +12.5pp
Anchor gapmodel − base
+17.9 pp
Crowd gapprice − base
+12.5 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 17.0% · AUC 0.752out-of-sample BSS (5-fold) 17.1% ± 3.0% · Brier 0.2074 · log-loss 0.6175 · n 1600✓ n = 1600
BrierBS
0.2074
lower = better · ō 0.50
BSSvs base
17.0%
improvement over base rate
ReliabilityREL
0.0073
miscalibration · want ↓
ResolutionRES
0.0495
decisiveness · want ↑
Log lossLL
0.6175
cross-entropy
AUCROC
0.752
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 1.03 · expectancy +0.013R180 trades · win 53.3% · Sharpe 0.013
Total P/Lnet
+$594
on $45,000 cycled
Win ratehit %
53.3%
96 W / 84 L
Profit factorPF
1.03
$ won / $ lost
Expectancyper trade
+$3.30
avg $ per position
R-expectancyper risk
+0.013R
in units of risk taken
Avg win / losspayoff
$224.94 / -$250.00
ratio 0.90 : 1
Sharpe / traderisk-adj
0.013
μR / σR
Closing line valueCLV
+2.41 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.