NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Lionel Messi attend UFC Freedom 250?
← 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-lionel-messi-attend-ufc-freedom-250-20260602162901358-787-497-734 page.
▼ NO EDGE YES · DO NOT TRADE
§1 · Position economics
YES · Expected P/L per share -0.0501@ model P(YES) = 0.180
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 0.00% · g(f★) = 0.000%deploy 0.00% · g = 0.000%
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 @ 0.231 · EV +$0stake $0 · 0.00% of bankroll
Deployed stakestake
$0
0.00% of bankroll
Sharesunits
0
each pays $1 if YES
Max payoutwin
$0
gross, if win
Max profitwin
+$0
net of cost
Max losslose
-$0
binary settles to $0
Payout multiple×
×4.34
$1 → $4.34
Risk:RewardR:R
3.34 : 1
win $3.34 per $1
Expected P/LE[P/L]
+$0
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 18.0% | +$0 | +$0 |
| Resolves against (lose) | 82.0% | -$0 | -$0 |
| Expected value | 100.0% | — | +$0 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion -5.0 pprelative edge -21.7%
Required win ratebreak-even
23.1%
price = implied probability
Model win rateP(win)
18.0%
what you forecast
Cushionedge
-5.0 pp
margin of safety
Fair pricemodel
0.180
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
23.1%
= price
Decimal oddsEU
4.338
total return per $1
AmericanUS
+334
$100 wins $334
FractionalUK
3.34 / 1
profit per $1 risked
Profit per $100stake
+$333.84
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR -378% · APY -99%ROI -21.7% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
-21.7%
APR (simple)scaled
-378%
ROI × 365/days
APY (compounded)if redeployed
-99%
(1+ROI)^(365/d) − 1
Daily expectedper day
-1.16%
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 -5.76 pperosion 0% · break-even w/ fees 23.8%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$0
0.00% · g = 0.000%
Half Kelly½ f★
$0
0.00% · g = 0.000%
Quarter Kelly¼ f★
$0
0.00% · g = 0.000%
Flat 1%1%
$250
1.00% · g = -0.231%
Flat 2%2%
$500
2.00% · g = -0.490%
Flat 5%5%
$1,250
5.00% · g = -1.419%
Recommended¼ f★
$0
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.779 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.681 bit
Δ -0.098 bit vs market
Surprise · YES−log₂ p
2.12 bit
self-information
Surprise · NO−log₂(1−p)
0.38 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0075 nat (0.0108 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 0.180 · CI [0.08, 0.31] · κ 40.1
Posterior meanE[θ]
0.180
Beta(7.2, 32.8)
95% credible intervalHDI
[0.08, 0.31]
price INSIDE → weak edge
Concentrationκ
40.1
pseudo-obs behind belief
Disagreementvs crowd
-5.0 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] -13.2% · P(YES) 20.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
-13.23%
P(YES) empiricalq
20.0%
Best pathmax
+333.8%
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 -0.12% · ruin rate 0.0%400 paths × 120 bets · f deploy 0.50%
Sharpe / betμ/σ
-0.130
μ -0.11% · σ 0.8%
Sortino / betμ/σ↓
-0.216
downside-only denominator
VaR 95%5%
-0.5%
per-bet worst-case
CVaR 95%ES
-0.5%
mean tail loss
Max drawdownMDD
-13.9%
Calmar -0.01
Ruin rate≤50%
0.0%
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 -34.6pp · crowd gap -29.5pp
Anchor gapmodel − base
-34.6 pp
Crowd gapprice − base
-29.5 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 24.2% · AUC 0.788out-of-sample BSS (5-fold) 24.3% ± 2.8% · Brier 0.1895 · log-loss 0.5604 · n 1600✓ n = 1600
BrierBS
0.1895
lower = better · ō 0.51
BSSvs base
24.2%
improvement over base rate
ReliabilityREL
0.0025
miscalibration · want ↓
ResolutionRES
0.0623
decisiveness · want ↑
Log lossLL
0.5604
cross-entropy
AUCROC
0.788
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 0.89 · expectancy -0.059R180 trades · win 47.8% · Sharpe -0.054
Total P/Lnet
-$2,648
on $45,000 cycled
Win ratehit %
47.8%
86 W / 94 L
Profit factorPF
0.89
$ won / $ lost
Expectancyper trade
-$14.71
avg $ per position
R-expectancyper risk
-0.059R
in units of risk taken
Avg win / losspayoff
$242.47 / -$250.00
ratio 0.97 : 1
Sharpe / traderisk-adj
-0.054
μR / σR
Closing line valueCLV
+2.55 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.