NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Seattle win the 2026 Pro Baseball Championship?
← 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/kalshi-kxmlb-26-sea page.
▲ YES EDGE · +0.002 · f★ 0.2% · deploy 0.1% · net -0.58pp
§1 · Position economics
YES · Expected P/L per share +0.0017@ model P(YES) = 0.098
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 0.19% · g(f★) = 0.002%deploy 0.10% · g = 0.001%
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 @ 0.096 · EV +$0stake $24 · 0.10% of bankroll
Deployed stakestake
$24
0.10% of bankroll
Sharesunits
251
each pays $1 if YES
Max payoutwin
$251
gross, if win
Max profitwin
+$227
net of cost
Max losslose
-$24
binary settles to $0
Payout multiple×
×10.42
$1 → $10.42
Risk:RewardR:R
9.42 : 1
win $9.42 per $1
Expected P/LE[P/L]
+$0
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 9.8% | +$227 | +$22 |
| Resolves against (lose) | 90.2% | -$24 | -$22 |
| 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 +0.2 pprelative edge +1.8%
Required win ratebreak-even
9.6%
price = implied probability
Model win rateP(win)
9.8%
what you forecast
Cushionedge
+0.2 pp
margin of safety
Fair pricemodel
0.098
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
9.6%
= price
Decimal oddsEU
10.417
total return per $1
AmericanUS
+942
$100 wins $942
FractionalUK
9.42 / 1
profit per $1 risked
Profit per $100stake
+$941.67
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 32% · APY 37%ROI 1.8% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+1.8%
APR (simple)scaled
+32%
ROI × 365/days
APY (compounded)if redeployed
+37%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.09%
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 -0.58 pperosion 431% · break-even w/ fees 10.4%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$48
0.19% · g = 0.002%
Half Kelly½ f★
$24
0.10% · g = 0.001%
Quarter Kelly¼ f★
$12
0.05% · g = 0.001%
Flat 1%1%
$250
1.00% · g = -0.027%
Flat 2%2%
$500
2.00% · g = -0.136%
Flat 5%5%
$1,250
5.00% · g = -0.857%
Recommended¼ f★
$12
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.456 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.462 bit
Δ +0.006 bit vs market
Surprise · YES−log₂ p
3.38 bit
self-information
Surprise · NO−log₂(1−p)
0.15 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0000 nat (0.0000 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 0.098 · CI [0.02, 0.24] · κ 23.5
Posterior meanE[θ]
0.098
Beta(2.3, 21.2)
95% credible intervalHDI
[0.02, 0.24]
price INSIDE → weak edge
Concentrationκ
23.5
pseudo-obs behind belief
Disagreementvs crowd
+0.2 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] +4.2% · P(YES) 10.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+4.17%
P(YES) empiricalq
10.0%
Best pathmax
+941.7%
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 0.01% · ruin rate 0.0%400 paths × 120 bets · f deploy 0.50%
Sharpe / betμ/σ
0.015
μ 0.02% · σ 1.6%
Sortino / betμ/σ↓
0.048
downside-only denominator
VaR 95%5%
-0.5%
per-bet worst-case
CVaR 95%ES
-0.5%
mean tail loss
Max drawdownMDD
-4.9%
Calmar 0.00
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 -30.7pp · crowd gap -30.9pp
Anchor gapmodel − base
-30.7 pp
Crowd gapprice − base
-30.9 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 18.8% · AUC 0.763out-of-sample BSS (5-fold) 19.1% ± 3.6% · Brier 0.2023 · log-loss 0.6040 · n 1600✓ n = 1600
BrierBS
0.2023
lower = better · ō 0.53
BSSvs base
18.8%
improvement over base rate
ReliabilityREL
0.0057
miscalibration · want ↓
ResolutionRES
0.0524
decisiveness · want ↑
Log lossLL
0.6040
cross-entropy
AUCROC
0.763
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 1.31 · expectancy +0.135R180 trades · win 56.1% · Sharpe 0.119
Total P/Lnet
+$6,074
on $45,000 cycled
Win ratehit %
56.1%
101 W / 79 L
Profit factorPF
1.31
$ won / $ lost
Expectancyper trade
+$33.74
avg $ per position
R-expectancyper risk
+0.135R
in units of risk taken
Avg win / losspayoff
$255.68 / -$250.00
ratio 1.02 : 1
Sharpe / traderisk-adj
0.119
μR / σR
Closing line valueCLV
+2.86 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.