NOSTRADAMUS · Position Analytics Engine
SIMULATOR Counter-Strike: FOKUS vs CYBERSHOKE Esports (BO3) - Stake Ranked Episode 3: Closed Qualifier Playoffs
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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-cs2-fokus-cs1-2026-06-20 page.
▲ YES EDGE · +0.002 · f★ 0.6% · deploy 0.3% · net -0.58pp
§1 · Position economics
YES · Expected P/L per share +0.0017@ model P(YES) = 0.737
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 0.65% · g(f★) = 0.001%deploy 0.32% · 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 @ 0.735 · EV +$0stake $81 · 0.32% of bankroll
Deployed stakestake
$81
0.32% of bankroll
Sharesunits
110
each pays $1 if YES
Max payoutwin
$110
gross, if win
Max profitwin
+$29
net of cost
Max losslose
-$81
binary settles to $0
Payout multiple×
×1.36
$1 → $1.36
Risk:RewardR:R
0.36 : 1
win $0.36 per $1
Expected P/LE[P/L]
+$0
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 73.7% | +$29 | +$22 |
| Resolves against (lose) | 26.3% | -$81 | -$21 |
| 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 +0.2%
Required win ratebreak-even
73.5%
price = implied probability
Model win rateP(win)
73.7%
what you forecast
Cushionedge
+0.2 pp
margin of safety
Fair pricemodel
0.737
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
73.5%
= price
Decimal oddsEU
1.361
total return per $1
AmericanUS
-277
risk $277 to win $100
FractionalUK
0.36 / 1
profit per $1 risked
Profit per $100stake
+$36.05
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 4% · APY 4%ROI 0.2% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+0.2%
APR (simple)scaled
+4%
ROI × 365/days
APY (compounded)if redeployed
+4%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.01%
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 437% · break-even w/ fees 74.3%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$162
0.65% · g = 0.001%
Half Kelly½ f★
$81
0.32% · g = 0.001%
Quarter Kelly¼ f★
$41
0.16% · g = 0.000%
Flat 1%1%
$250
1.00% · g = 0.001%
Flat 2%2%
$500
2.00% · g = -0.003%
Flat 5%5%
$1,250
5.00% · g = -0.034%
Recommended¼ f★
$41
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.834 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.832 bit
Δ -0.003 bit vs market
Surprise · YES−log₂ p
0.44 bit
self-information
Surprise · NO−log₂(1−p)
1.92 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 0.737 · CI [0.61, 0.85] · κ 52.9
Posterior meanE[θ]
0.737
Beta(39.0, 13.9)
95% credible intervalHDI
[0.61, 0.85]
price INSIDE → weak edge
Concentrationκ
52.9
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] +3.7% · P(YES) 76.3% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+3.74%
P(YES) empiricalq
76.3%
Best pathmax
+36.1%
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 -0.00% · ruin rate 0.0%400 paths × 120 bets · f deploy 0.50%
Sharpe / betμ/σ
0.002
μ 0.00% · σ 0.3%
Sortino / betμ/σ↓
0.001
downside-only denominator
VaR 95%5%
-0.5%
per-bet worst-case
CVaR 95%ES
-0.5%
mean tail loss
Max drawdownMDD
-0.8%
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 +17.1pp · crowd gap +16.9pp
Anchor gapmodel − base
+17.1 pp
Crowd gapprice − base
+16.9 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 22.1% · AUC 0.777out-of-sample BSS (5-fold) 22.1% ± 2.2% · Brier 0.1947 · log-loss 0.5787 · n 1600✓ n = 1600
BrierBS
0.1947
lower = better · ō 0.49
BSSvs base
22.1%
improvement over base rate
ReliabilityREL
0.0040
miscalibration · want ↓
ResolutionRES
0.0591
decisiveness · want ↑
Log lossLL
0.5787
cross-entropy
AUCROC
0.777
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 0.99 · expectancy -0.005R180 trades · win 47.8% · Sharpe -0.004
Total P/Lnet
-$212
on $45,000 cycled
Win ratehit %
47.8%
86 W / 94 L
Profit factorPF
0.99
$ won / $ lost
Expectancyper trade
-$1.18
avg $ per position
R-expectancyper risk
-0.005R
in units of risk taken
Avg win / losspayoff
$270.80 / -$250.00
ratio 1.08 : 1
Sharpe / traderisk-adj
-0.004
μR / σR
Closing line valueCLV
+3.61 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.