POLYMARKET · PREDICTION MARKET · SPORTS

Will Romelu Lukaku be the top goalscorer at the 2026 FIFA World Cup?

YES · live
0.3¢
NO · live
99.8¢

▸ Advanced metrics · M2M bundle

polymarket · will-romelu-lukaku-be-the-top-goalscorer-at-the-2026-fifa-world-cup · fresh · feed 10s old
24h sparkline · 60 pts▼ —
realized vol (ann.)
5.63%
max drawdown
0.00%
sharpe
—
ulcer index
0.00%
RMS drawdown
pain index
0.00%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
0.00%
cond. drawdown
gain/pain
—
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
—
upside/downside
roll spread
21.0 bps
implied (price-only)
bars used
553
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API: /api/m2m/pm-will-romelu-lukaku-be-the-top-goalscorer-at-the-2026-fifa-world-cup/bundle · venue execution: polymarket →
LIVEPOLL0SRCFRESH9.6s⏱--:--:-- UTC8NEXT8.0sUP0s--:--HIST0/30
▶ STREAMING·HYPERLIQUID·POLYMARKET·0 POLLS·SRC FRESH·UPTIME 0s·NEXT POLL 8.0s·CC0 OPEN DATA·HYPO.MARKETS·▶ STREAMING·HYPERLIQUID·POLYMARKET·0 POLLS·SRC FRESH·UPTIME 0s·NEXT POLL 8.0s·CC0 OPEN DATA·HYPO.MARKETS·
YES · live
0.3¢
NO · live
99.8¢
YES price · live 24h
n=25 · μ=0.0020 · σ=0.0008 · range [0.0015, 0.0035] · R²=0.498▼ FALLING -28.57%σ EXTREME 38.13%LAST 0.00250.00350.00300.00250.00200.0015μ = 0.0020max 0.0035min 0.0015dataMA(5)OLS R²=0.50μ lineμ ± σ bandmaxminlive endpoint
25 ticks · last 0.25¢
YES / NO split · live
YES 0.3%NO 99.8%NO99.8%99.75¢ · odds 1/1.00
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.025 / 1.00 bits (3%) · informative — one side favoured
YES
0.3%0.3¢400.00×▬ +0.00pp
NO
99.8%99.8¢1.00×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Per-tick activity · |Δp| in basis points · live
n=24 · Σ=50 · μ=2.1 · σ=4.1 · CV=1.99BURSTY · concentratedcumulative energy ↗ · 50% by h=7035810μ = 21050%h1h5h9h13h17h21#1 peak#2-3> μactivequietμ linecum energy
Σ 50bp moved · peak 10bp · n=24 ticks
Live numerics · pulse on poll
LIVE NUMERICS8 metrics·POLL 0
⏱snapshot age
9.6s
▲YES mid
0.25¢ (0.25%)
▼NO mid
99.75¢ (99.75%)
ΣΣ sides
100.00%
⚖arb gap
0.000pp
$24h vol $
$110.8k
≋liquidity $
$58.1k
◳history points
25 ticks (live)

§1 · 24h price history (YES + NO tokens)

YES price · CLOB mid
n=25 · μ=0.0020 · σ=0.0008 · range [0.0015, 0.0035] · R²=0.498▼ FALLING -28.57%σ EXTREME 38.13%LAST 0.00250.00350.00300.00250.00200.0015μ = 0.0020max 0.0035min 0.0015dataMA(5)OLS R²=0.50μ lineμ ± σ bandmaxmin
25 YES observations from clob.polymarket.com · last 0.25¢
NO price · CLOB mid
n=25 · μ=0.9980 · σ=0.0008 · range [0.9965, 0.9985] · R²=0.498▲ RISING +0.10%σ LOW 0.08%LAST 0.99750.99850.99800.99750.99700.9965μ = 0.9980max 0.9985min 0.9965dataMA(5)OLS R²=0.50μ lineμ ± σ bandmaxmin
25 NO observations from clob.polymarket.com · last 99.75¢

§2 · Distribution of Δp

Histogram of hourly increments
n=24 · 10 bins · μ=0.0000 · σ=0.0004 · skew=-0.70 (left-skewed) · kurt=1.69 (leptokurtic (fat tails))191410503-0.09ppbin -0.09pp · n=3 · 15.8% peakbin -0.09pp · n=3 · 15.8% peak-0.07pp-0.05pp-0.03pp-0.01pp190.01ppbin 0.01pp · n=19 · 100.0% peakbin 0.01pp · n=19 · 100.0% peak0.03pp0.05pp0.07pp20.09ppbin 0.09pp · n=2 · 10.5% peakbin 0.09pp · n=2 · 10.5% peakμΔ < 0 · loss barsΔ ≈ 0 · flatΔ > 0 · gain barsN(μ,σ²) referenceμ line · ±σ band shaded
n=24
Q-Q plot · standardised Δp vs N(0,1)
n=24 · skew=-0.17 · kurt=1.77 · near 8 / mid 14 / far 2 · OLS slope=0.81 intercept=-0.00MODERATE DEPARTURE · SOME OUTLIERSUPPER TAIL NORMALLOWER TAIL NORMAL-3σ-3σ-2σ-2σ-1σ-1σ+0σ+0σ+1σ+1σ+2σ+2σ+3σ+3σsample ↓marginal: sample bars + theoretical N(0,1) curve →theoretical Φ⁻¹(p) →↑ sample z-quantile|Δ| < 0.3σ · on the line|Δ| < 1σ · moderate|Δ| ≥ 1σ · outliery = x refOLS fit
reference line = identity (perfect normality). Heavy upper-right tail = fat positive tail.

§3 · Sample moments

Descriptive statistics · 5-number summary · shape diagnostics
SAMPLE MOMENTS · N=25RIGHT-SKEWED (G₁=0.99)
μ MEAN0.20¢95% CI: [0.17¢, 0.23¢]
σ STD DEV0.08ppσ² = 59.333×10⁻⁴ · CV = 38.13%
med MEDIAN0.15¢Q₁ 0.15¢ · Q₃ 0.25¢
FIVE-NUMBER SUMMARY · BOX PLOTrange 0.20pp · IQR 0.10pp (1.349σ→0.10pp)
min 0.15¢Q₁ 0.15¢med 0.15¢Q₃ 0.25¢max 0.35¢μ
SKEWNESS · G₁0.986right-skewed
−3−10+1+3
EXCESS KURTOSIS · G₂-0.656mesokurtic · normal-like
−30+2+4+6
μ ↔ medianμ > med · right-tailed|μ−med| / σ = 0.68
σ × 1.349 ↔ IQRconsistent with normalratio = 1.04
range ↔ σconcentrated (range < 4σ)range / σ = 2.60
μ = mean YES probability · σ = standard deviation · 95% CI = μ ± 1.96·SE. Skew/kurt diagnose departure from normality.

§5 · Time-series structure

Regime & autocorrelation diagnostics
TIME-SERIES STRUCTUREREGIME: MEAN-REVERTING · ρ(1) -0.22 + ADF rejected
ρ(1) AUTOCORR-0.219within white-noise band
ρ(2) AUTOCORR-0.018lag-2 not significant
H · HURST EXPONENT1.290strongly persistent
OLS TREND · t-STAT-4.775significant @ α=0.05
HURST EXPONENT [0, 1]strongly persistent · H = 1.290
H = 1.290STRONGLY PERSISTENT
0
anti-persistent0.45
mean-reverting0.5
random walk0.55
persistent1
strongly trending
AUTOCORRELATION FUNCTION · ρ(k) for k=1..5WHITE NOISE · no significant lags
k=1-0.219k=2-0.018k=3-0.018k=4-0.010k=5+0.1920+1−1+0.41−0.41+ momentum (ρ > +0.41)− reversal (ρ < −0.41)noise (within band)±2/√n threshold
OLS TREND · t-STAT · [-5, +5]SIGNIFICANT @ 1% (|t|=4.78)
−5 reject−1.960 retain H₀+1.96+5 reject
REGIME CLASSIFICATIONMEAN-REVERTING · ρ(1) -0.22 + ADF rejectedfrom Hurst + ρ(1) joint diagnosis
PREDICTABILITY · score 1.00very high · strong structure|ρ(1)| + 2·|H − 0.5| heuristic
TREND SIGNIFICANCESIGNIFICANT @ 1% (|t|=4.78)α=0.05 critical |t|=1.96 · α=0.01 |t|=2.58
ρ(k) = lag-k sample autocorrelation · H = R/S Hurst exponent · t = OLS-trend t-statistic. Significance bands at ±2/√n approximate the 95% white-noise envelope. α=0.05 critical |t|=1.96; α=0.01 |t|=2.58.

§6 · Microstructure

Market quality · two-sided pricing · activity
MICROSTRUCTURE · MARKET QUALITYPERFECT · ARB-FREE Σ=100.00%
MARKET ID2069690
SLUGwill-romelu-luka…fa-world-cup
CATEGORYSports
TWO-SIDED PRICINGFAVOURS NO (100¢)
PRIMARY · YES0.25¢implied prob 0.25% · decimal odds 400.00×
COUNTER · NO99.75¢implied prob 99.75% · decimal odds 1.00×
0.25¢
99.75¢
Σ-SIDES ARBITRAGE TESTPERFECT · ARB-FREE Σ=100.00%
0%50%100% · target110%
Σ = 100.00% · |1 − Σ| = 0.000pp
24H ACTIVITY · LIQUIDITYDEEP
24H VOLUME110.82k USD 24h
LIQUIDITY58.07k USD
MARKET QUALITYPERFECT · ARB-FREE Σ=100.00%|1−Σ| ≤ 0.5pp ⇒ fair · > 2pp ⇒ inefficient
PRICING SKEWFAVOURS NO (100¢)|primary − counter| = 0.995 · entropy 0.025 bits
LIQUIDITY DEPTHDEEP100k+ deep · 10k+ active · 1k+ modest · 100+ thin
Σ-sides = YES + NO implied probabilities. Perfect arb-free Σ = 100%. |1−Σ| > 2pp suggests synthetic outright arbitrage.

§7 · Position sizing & edge analysis

Probability split · YES vs NO · Kelly · entropy · arbitrage
FAIR MARKET · no edge
YES 0.3%NO 99.8%YES p̂0.3%H = 0.025 / 1.00 bits
Probability scale (YES)
0%25%50%
fair75%100%
Implied decimal odds
YES400.00×(0¢)NO1.00×(100¢)
Kelly bet-size (% of bankroll) K* = 0.00%
K* full
0.00%
½K half
0.00%
¼K quarter
0.00%
Entropy H(p̂) = 0.025 bits (3% of max) · informative — one side strongly favoured
0 (certain)0.250.50.751.00 (max)
Σ-sides = 100.00% · |1 − Σ| = 0.00pp · tight cross-venue rounding
K* full = (b·p − q)/b · ½K and ¼K are conservative fractions of the full-Kelly bet. Entropy in bits — log₂(2)=1 is maximum uncertainty for a binary market.

§8 · Time decay & θ projection

Time decay & theta projection
⏱ URGENCY · DISTANTresolves 2026-07-20 00:00 UTC
29days
14hrs
19min
29.60 days·θ = 0.377 pp/day
YES →$1.00(P = 0.3%)
NO →$0.00(P = 99.8%)
current: $0.0025 · expected return per side: $1.00 on YES hit · $0.00 on NO hit
0%25%50%75%100%YES $1NO $0NOW+14.8dRESOLVESP projection · σ=0.08% · path funnel to settle at YES=1 or NO=0
Theta progression · θ ∝ σ / √t_remainingθ_now = 0.377 pp/day
now29.60d left
0.377 pp/day×1.00
−25%22.20d left
0.436 pp/day×1.15
−50%14.80d left
0.534 pp/day×1.41
−75%7.40d left
0.755 pp/day×2.00
−90%2.96d left
1.193 pp/day×3.16
θ approximation: σ/√T (expected daily move magnitude). The cone shows ±√(p̂(1−p̂)) widening as time decays, funneling to {0, 1} at resolution. Theta accelerates as √(t_left)→0.

§9 · Hourly return heatmap

24-hour signed Δp grid · green = up · red = down
HOURLY RETURN HEATMAP · n=24 bars · best 0.10% · worst -0.10% · typical |Δ| 0.02%MILD BEARISH -0.10%BEST+0.10%7hWORST-0.10%4hTYPICAL |Δ|0.02%mean absoluteCUMULATIVE-0.10%Σ signed ΔSTREAK↗ 1up-runASIA · 00-08 UTCμ -0.01% · Σ -0.10%EUROPE · 08-16 UTCμ -0.01% · Σ -0.10%US · 16-24 UTCμ +0.00% · Σ +0.00%CUMULATIVE Δ PATH · final -0.10%+0.00%-0.20%0.00% · 1h0.00% · 1h·1h0.00% · 2h0.00% · 2h·2h0.00% · 3h0.00% · 3h·3h-0.10% · 4h-0.10% · 4h-0.10%4h▼ WORST0.00% · 5h0.00% · 5h·5h-0.10% · 6h-0.10% · 6h-0.10%6h0.10% · 7h0.10% · 7h0.10%7h★ BEST0.00% · 8h0.00% · 8h·8h-0.10% · 9h-0.10% · 9h-0.10%9h0.00% · 10h0.00% · 10h·10h0.00% · 11h0.00% · 11h·11h0.00% · 12h0.00% · 12h·12h0.00% · 13h0.00% · 13h·13h0.00% · 14h0.00% · 14h·14h0.00% · 15h0.00% · 15h·15h0.00% · 16h0.00% · 16h·16h0.00% · 17h0.00% · 17h·17h0.00% · 18h0.00% · 18h·18h0.00% · 19h0.00% · 19h·19h0.00% · 20h0.00% · 20h·20h0.00% · 21h0.00% · 21h·21h0.00% · 22h0.00% · 22h·22h0.00% · 23h0.00% · 23h·23h0.10% · 24h0.10% · 24h0.10%24hTIME PATTERNuniform across sessionsRUNSup max 1 · down max 1BREADTH8% up · 13% down · 79% flat
2 up bars · 3 down · best 0.10% · worst -0.10% · typical |Δ| 0.021%

§10 · Equity curve & underwater drawdown

Cumulative compounded return + running peak-to-trough
EQUITY & DRAWDOWN ANALYSIS · n=25 barsLOSS · SHALLOW DD (-0.10%)FINAL-0.10%MAX DD-0.20%RECOVERYONGOING · 21 barsMAX RUN-UP+0.00%UNDERWATER21/25 (84%)STREAK↗ 1EQUITY CURVE · end 0.9990 · peak 1.0000 · range [0.9980, 1.0000]1.00000.9980break-even = 1★ PEAK 1.0000UNDERWATER DRAWDOWN · max -0.20% · shallow0%-0.20%▼ TROUGH -0.20%TOP DRAWDOWN PERIODS · 1 total#1 -0.20%bar 5-25 · 21 bars · ONGOINGDD SEVERITYshallow (max -0.20%)RECOVERYongoing · 21 barsTIME UNDER WATER84% of session · 21/25 bars
final equity 0.9990 (-0.10%) · max DD -0.20% · time-under-water 21/25 bars

§11 · Rolling-window statistics (w = 6 bars)

Rolling annualised Sharpe ratio · green positive · red negative
n=19 · +1 / −8 (5% positive) · μ=-11.56 · σ=21.94UNPROFITABLE STRATEGYLAST 38.21 (+2.27σ vs μ)60.4230.210.00-30.21-60.42μ = -11.56-60.42-60.42-20.72-20.72-20.72-20.72-38.21-38.21-20.72-20.72-20.72-20.720.000.00-38.21-38.21-38.21-38.210.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.000.0038.2138.21v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest 38.210 · range [-60.42, 38.21] · μ -11.564 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
Rolling annualised volatility (%)
n=19 · μ=3.0547 · σ=3.1786 · range [0.0000, 7.6420] · R²=0.619▼ FALLING -20.94%σ EXTREME 104.06%LAST 3.82107.64205.73153.82101.91050.0000μ = 3.0547max 7.6420min 0.0000dataMA(3)OLS R²=0.62μ lineμ ± σ bandmaxmin
latest 3.82% · range [0.00%, 7.64%] · μ 3.05% · σ̂ scaled to annualised (×√8760)
Rolling lag-1 autocorrelation ρ(1)
n=19 · +0 / −9 (0% positive) · μ=-0.140 · σ=0.187MEAN-REVERSIONLAST -0.033 (+0.57σ vs μ)0.4800.2400.000-0.240-0.480μ = -0.140-0.333-0.333-0.480-0.480-0.422-0.422-0.333-0.333-0.422-0.422-0.363-0.3630.0000.000-0.233-0.233-0.033-0.0330.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000-0.033-0.033v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -0.033 · |ρ| > 0.3 ⇒ regime with persistence (ρ > 0) or reversal (ρ < 0) · |ρ| ≤ 0.1 = consistent with random walk

§12 · Hypothesis tests (α = 0.05)

Formal inference at 5% significance
2 of 6 REJECT · mixed evidence2 reject·4 pass·α = 0.05
𝒩

Jarque-Bera

REJECT H₀*

H₀: Δp ~ Normal(μ, σ²)

STATISTIC
6.3802
p-VALUE (log scale)
0.0412
α
10⁻⁴10⁻³10⁻²10⁻¹1
p < α · rejection zonenon-normal · fat tails or skew present
ρ

Ljung-Box(h=5)

FAIL TO REJECTns

H₀: No serial autocorrelation up to lag 5

STATISTIC
2.5252
p-VALUE (log scale)
0.7749
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedconsistent with white noise
Ψ

Dickey-Fuller (τ_μ)

FAIL TO REJECTns

H₀: p has a unit root (non-stationary)

STATISTIC
-2.1712
p-VALUE (log scale)
0.2245
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedrandom-walk behaviour (crit ≈ -2.86)
±

Wald-Wolfowitz runs

FAIL TO REJECTns

H₀: Sign sequence of Δ is random

STATISTIC
0.6547
p-VALUE (log scale)
0.5127
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedsigns appear random (4 runs)
χ

KPSS (μ stationarity)

REJECT H₀*

H₀: p IS level-stationary

STATISTIC
0.6155
p-VALUE (log scale)
0.0212
α
10⁻⁴10⁻³10⁻²10⁻¹1
p < α · rejection zonenon-stationary (crit 0.463)
χ

Variance ratio q=3

FAIL TO REJECTns

H₀: Δp is a random walk · VR = 1

STATISTIC
-1.3836
p-VALUE (log scale)
0.1665
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedVR 0.579 ≈ 1 (RW behaviour)
Each row states an explicit null H₀, the test statistic, an approximated p-value, and the decision. REJECT means evidence against H₀. KPSS complements ADF (rejecting both ⇒ ambiguous; rejecting one ⇒ clean verdict).

§13 · Spectral analysis (DFT periodogram)

Power spectrum of Δp · ‖X̂(k)‖²/n
n=12 bins · noise floor μ=2.08e-7 · top T=2.40h (22.0%) · top-3 cover 50.0%1 SIGNIFICANT CYCLEcumulative energy ↗ (1 bin above 2× noise)5.5e-74.1e-72.7e-71.4e-70.0e+0μ noise floor2× noise (significance)period 24.0 · power 1.45e-7 · 5.8% energyperiod 24.0 · power 1.45e-7 · 5.8% energyperiod 12.0 · power 1.17e-7 · 4.7% energyperiod 12.0 · power 1.17e-7 · 4.7% energyperiod 8.0 · power 1.74e-7 · 7.0% energyperiod 8.0 · power 1.74e-7 · 7.0% energyperiod 6.0 · power 2.92e-7 · 11.7% energyperiod 6.0 · power 2.92e-7 · 11.7% energyperiod 4.8 · power 8.62e-8 · 3.4% energyperiod 4.8 · power 8.62e-8 · 3.4% energyperiod 4.0 · power 2.08e-7 · 8.3% energyperiod 4.0 · power 2.08e-7 · 8.3% energyperiod 3.4 · power 2.47e-7 · 9.9% energyperiod 3.4 · power 2.47e-7 · 9.9% energyperiod 3.0 · power 4.17e-8 · 1.7% energyperiod 3.0 · power 4.17e-8 · 1.7% energyperiod 2.7 · power 4.10e-7 · 16.4% energyperiod 2.7 · power 4.10e-7 · 16.4% energyperiod 2.4 · power 5.50e-7 · 22.0% energyperiod 2.4 · power 5.50e-7 · 22.0% energyperiod 2.2 · power 1.88e-7 · 7.5% energyperiod 2.2 · power 1.88e-7 · 7.5% energyperiod 2.0 · power 4.17e-8 · 1.7% energyperiod 2.0 · power 4.17e-8 · 1.7% energy50% by T=3.4h#1 dominantT=2.40h#2T=2.67h#3T=6.00hT=2hT=3hT=4hT=6hT=8hT=12hT=16hT=24h← shorter cycle (high freq · Nyquist=½) · period T (bars per cycle) · longer cycle (low freq · 1/n) →#1 dominant#2 peak#3 peak> 2× noisenoiseμ floor2μ sig.cum energy
dominant period ≈ 2.40h (freq 0.417) · concentrates 22.0% of total energy · Σ|X̂|²/n = 2.500e-6

▸ Depth section using sovereign-store price series (4203 bars · effective 1752518 bars/year) — annualisation reflects native polling cadence, not upstream timeframes.

§14 · Honest position analytics

A binary-market analytics module framed in horizon time (days to resolution, not annualised). Estimators that need a model probability q as a first-class input (Kelly, KL divergence, Bayesian posterior, Mark-to-Market MC) only render when q is provided externally. Sweep an exploratory q at the interactive simulator →

§15 · Horizon returns

Returns · per bar / per day / per horizon
Horizon 29.6 d · σ/bar 0.017pp · expected |Δp| over horizon 0.45ppterminal variance p(1−p) = 0.0025 · n = 4203✓ n = 4203
μ per bar
-0.000pp
average Δp · drift
σ per bar
0.017pp
one-bar volatility · logit-free
Per-day movedaily
0.08pp
σ × √24
Per-horizon move30d
0.45pp
σ × √710.3200283333333
Terminal variancebinary
0.0025
p(1−p) at resolution
Current pricep
0.3¢
latest snapshot
Note: annualised Sharpe/Sortino are omitted — they are not meaningful for a bounded fixed-horizon binary contract that snaps to {0, 1} at resolution.
Annualised metrics are intentionally omitted — they don't apply to bounded probability series that resolve at a fixed date.

§16 · Tail risk

VaR · ES · max drawdown
VaR₉₅ 0.03pp · ES₉₅ 0.03pp · method parametric · drift-correcteddrift -0.000pp/bar · quantised: yes · median step 0.10pp · unique ratio 0.00✓ n = 4203
VaR 95%
0.03pp
1.645·σ (parametric) of Δp
ES 95%
0.03pp
mean of the tail
Max drawdown
88.9pp
peak 1.4¢ → trough 0.1¢
Median step
0.10pp
price bucket granularity
Price series is bucketed (cent grid). Empirical quantiles collapse to grid points — parametric N(0, σ²) used instead.
Empirical quantiles unless the price series is bucketed (PM cent grid), in which case parametric N(0, σ²) is used to avoid grid collapse.

§17 · Odds conversion

Odds conversion · every dialect a bettor thinks in
Implied probabilityP
0.3%
= price
Decimal oddsEU
400.000
total return per $1
AmericanUS
+39900
$100 wins $39900
FractionalUK
399.00 / 1
profit per $1 risked
Profit per $100stake
+$39900.00
clean dollar framing
-1000-5000+500+1000020406080100you · 0.3%implied probability (%)American odds
underdog (+)favorite (-)your price
Price → implied probability → decimal odds → American moneyline → fractional. Five views of the same number, plus the moneyline curve.

§18 · Binary entropy

Binary entropy · uncertainty as bits of information
Market entropyH(p)
0.025 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.025 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
8.64 bit
self-information
Surprise · NO−log₂(1−p)
0.00 bit
self-information
0.000.260.530.791.050.00.20.40.60.81.0marketmodelprobabilityH (bits)
Market entropy only — model entropy requires an external q.

§19 · Model-dependent surfaces

§ Edge / Kelly / KL · no model probability provided

External model required

The position-economics, Kelly, KL-divergence, Bayesian and Monte-Carlo surfaces require a model probability q as input — a number independent of the market price p.

The previous build defaulted q to a tape-momentum heuristic derived from p; that produces apparent edge that is structurally guaranteed to be small and is not a useful skill signal. The auto-derived path has been removed.

To explore these surfaces with a hypothetical q, open the interactive simulator and drag the MODEL P(YES) slider. To wire a real model, POST to the NOSTRADAMUS hook (TBD) or pass ?q=… on the simulator URL.

§∞ · Provenance & attestation

Upstream (snapshot)
gamma-api.polymarket.com
Upstream (history)
clob.polymarket.com
YES token ID
89356264212518287137287905381417541374034867415949008230668270452372265703593
NO token ID
59752744251413310452815821387975196320124895226973612999284310086076845395871
Snapshot fetched
2026-06-20 09:40:38 UTC
Snapshot age
9.6s
History points
25 CLOB mids
Page rendered
2026-06-20 09:40:47 UTC
Storage policy
no persistence — fetched on every request
SHA-256 attestation
7c303dd70d7405b59121445f5bfe304224fe3b66264f0bcefc64db15553e248b · deterministic hash of source snapshot
Open data licence
CC0 / public domain

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Also see: /arb opportunities · RSS feed · more in Sports

Market depth

▸ live order book · Polymarket YES
Depth within 1bp
$0
bid $0 · ask $0
Depth within 5bp
$0
bid $0 · ask $0
Depth within 10bp
$0
bid $0 · ask $0
Depth within 50bp
$0
bid $0 · ask $0
Mid price
0.002500
(best bid + best ask) / 2
Spread
4000.0bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
-0.994
ask-heavy
Imbalance (top-5)
-0.092
ask-heavy top-of-book

Slippage scenarios

▸ live book walk · Polymarket YES

Simulating a market order at three notionals against the live book. Slippage = avg execution price vs. mid, in basis points. Worst fill = price of the deepest level touched. Live JSON: /api/asset/pm-will-romelu-lukaku-be-the-top-goalscorer-at-the-2026-fifa-world-cup/slippage?size=10000&side=buy

SideNotionalAvg fillSlippageWorst fillLevelsStatus
BUY$1.00K0.02321982875.42bp0.20700030FILLED
BUY$10.00K0.177889701554.89bp0.89900047FILLED
BUY$100.00K0.6797292708917.34bp0.99900082FILLED
SELL$1.00K0.0010025990.67bp0.0010002PARTIAL
SELL$10.00K0.0010025990.67bp0.0010002PARTIAL
SELL$100.00K0.0010025990.67bp0.0010002PARTIAL

Risk metrics

▸ sovereign store · 4,203 barsperiods/year ≈ 1.75M
Realized vol (annualised)
5105.68%
σ per bar = 0.038568
Mean return (annualised)
-70334.25%
μ per bar = -0.000401
Sharpe (rf=0)
-13.78
annualised; risk-free assumed zero
Max drawdown
88.89%
peak 0.01 → trough 0.00 over 13 bars

/api/asset/pm-will-romelu-lukaku-be-the-top-goalscorer-at-the-2026-fifa-world-cup/risk · same metrics, JSON