NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Sam Burns win the RBC Canadian Open?
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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/kalshi-kxpgatour-rbbcan26-sbur page.
▼ NO EDGE YES · DO NOT TRADE
§1 · Position economics
YES · Expected P/L per share -0.0282@ model P(YES) = 0.044
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 @ 0.072 · 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×
×13.89
$1 → $13.89
Risk:RewardR:R
12.89 : 1
win $12.89 per $1
Expected P/LE[P/L]
+$0
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 4.4% | +$0 | +$0 |
| Resolves against (lose) | 95.6% | -$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 -2.8 pprelative edge -39.1%
Required win ratebreak-even
7.2%
price = implied probability
Model win rateP(win)
4.4%
what you forecast
Cushionedge
-2.8 pp
margin of safety
Fair pricemodel
0.044
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
7.2%
= price
Decimal oddsEU
13.889
total return per $1
AmericanUS
+1289
$100 wins $1289
FractionalUK
12.89 / 1
profit per $1 risked
Profit per $100stake
+$1288.89
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR -680% · APY -100%ROI -39.1% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
-39.1%
APR (simple)scaled
-680%
ROI × 365/days
APY (compounded)if redeployed
-100%
(1+ROI)^(365/d) − 1
Daily expectedper day
-2.34%
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 -3.57 pperosion 0% · break-even w/ fees 7.9%
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 = -0.430%
Flat 2%2%
$500
2.00% · g = -0.926%
Flat 5%5%
$1,250
5.00% · g = -2.724%
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)
0.373 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.260 bit
Δ -0.114 bit vs market
Surprise · YES−log₂ p
3.80 bit
self-information
Surprise · NO−log₂(1−p)
0.11 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0068 nat (0.0099 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 0.044 · CI [0.00, 0.22] · κ 10.6
Posterior meanE[θ]
0.044
Beta(0.5, 10.2)
95% credible intervalHDI
[0.00, 0.22]
price INSIDE → weak edge
Concentrationκ
10.6
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] -37.5% · P(YES) 4.5% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
-37.50%
P(YES) empiricalq
4.5%
Best pathmax
+1288.9%
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 -0.16% · ruin rate 0.0%400 paths × 120 bets · f deploy 0.50%
Sharpe / betμ/σ
-0.073
μ -0.12% · σ 1.6%
Sortino / betμ/σ↓
-0.232
downside-only denominator
VaR 95%5%
-0.5%
per-bet worst-case
CVaR 95%ES
-0.5%
mean tail loss
Max drawdownMDD
-18.0%
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 -37.9pp · crowd gap -35.1pp
Anchor gapmodel − base
-37.9 pp
Crowd gapprice − base
-35.1 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 18.7% · AUC 0.759out-of-sample BSS (5-fold) 18.8% ± 1.1% · Brier 0.2031 · log-loss 0.6016 · n 1600✓ n = 1600
BrierBS
0.2031
lower = better · ō 0.49
BSSvs base
18.7%
improvement over base rate
ReliabilityREL
0.0039
miscalibration · want ↓
ResolutionRES
0.0506
decisiveness · want ↑
Log lossLL
0.6016
cross-entropy
AUCROC
0.759
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 1.08 · expectancy +0.037R180 trades · win 53.9% · Sharpe 0.035
Total P/Lnet
+$1,679
on $45,000 cycled
Win ratehit %
53.9%
97 W / 83 L
Profit factorPF
1.08
$ won / $ lost
Expectancyper trade
+$9.33
avg $ per position
R-expectancyper risk
+0.037R
in units of risk taken
Avg win / losspayoff
$231.23 / -$250.00
ratio 0.92 : 1
Sharpe / traderisk-adj
0.035
μR / σR
Closing line valueCLV
+3.10 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.