POLYMARKET · PREDICTION MARKET · SPORTS

Will Kimi Antonelli win the 2026 F1 Catalunya Grand Prix?

YES · live
0.1¢
NO · live
100.0¢

▸ Advanced metrics · M2M bundle

polymarket · f1-catalunya-grand-prix-winner-antonelli-2026-06-14 · fresh · feed 0s old
realized vol (ann.)
—
max drawdown
—
sharpe
—
ulcer index
—
RMS drawdown
pain index
—
mean drawdown
mod. VaR 95%
—
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
—
cond. drawdown
gain/pain
—
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
—
upside/downside
roll spread
—
implied (price-only)
bars used
0
insufficient
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 0%
  • insufficient history for risk metrics — directional read only
Same bundle via M2M API: /api/m2m/pm-f1-catalunya-grand-prix-winner-antonelli-2026-06-14/bundle · venue execution: polymarket →
LIVEPOLL0SRCFRESH6ms⏱--:--:-- 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
0.1¢
NO · live
100.0¢
YES price · live 24h
n=24 · μ=0.1868 · σ=0.0993 · range [0.0005, 0.2650] · R²=0.544▼ FALLING -99.78%σ EXTREME 53.16%LAST 0.00050.26500.19890.13280.06660.0005μ = 0.1868max 0.2650min 0.0005dataMA(4)OLS R²=0.54μ lineμ ± σ bandmaxminlive endpoint
24 ticks · last 0.05¢
YES / NO split · live
YES 0.1%NO 100.0%NO100.0%99.95¢ · odds 1/1.00
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.006 / 1.00 bits (1%) · informative — one side favoured
YES
0.1%0.1¢2000.00×▬ +0.00pp
NO
100.0%100.0¢1.00×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Per-tick activity · |Δp| in basis points · live
n=23 · Σ=4,255 · μ=185.0 · σ=350.6 · CV=1.90BURSTY · concentratedcumulative energy ↗ · 50% by h=1804118231,2341,645μ = 1851,64550%h1h4h7h10h13h16h19h22#1 peak#2-3> μactivequietμ linecum energy
Σ 4255bp moved · peak 1645bp · n=23 ticks
Live numerics · pulse on poll
LIVE NUMERICS8 metrics·POLL 0
⏱snapshot age
6ms
▲YES mid
0.05¢ (0.05%)
▼NO mid
99.95¢ (99.95%)
ΣΣ sides
100.00%
⚖arb gap
0.000pp
$24h vol $
$140.3k
≋liquidity $
$30.0k
◳history points
24 ticks (live)

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

YES price · CLOB mid
n=24 · μ=0.1868 · σ=0.0993 · range [0.0005, 0.2650] · R²=0.544▼ FALLING -99.78%σ EXTREME 53.16%LAST 0.00050.26500.19890.13280.06660.0005μ = 0.1868max 0.2650min 0.0005dataMA(4)OLS R²=0.54μ lineμ ± σ bandmaxmin
24 YES observations from clob.polymarket.com · last 0.05¢
NO price · CLOB mid
n=25 · μ=0.8209 · σ=0.1039 · range [0.7350, 0.9995] · R²=0.597▲ RISING +28.97%σ HIGH 12.66%LAST 0.99950.99950.93340.86730.80110.7350μ = 0.8209max 0.9995min 0.7350dataMA(5)OLS R²=0.60μ lineμ ± σ bandmaxmin
25 NO observations from clob.polymarket.com · last 99.95¢

§2 · Distribution of Δp

Histogram of hourly increments
n=23 · 10 bins · μ=-0.0127 · σ=0.0356 · skew=-2.93 (left-skewed) · kurt=8.62 (leptokurtic (fat tails))13107301-15.48ppbin -15.48pp · n=1 · 7.7% peakbin -15.48pp · n=1 · 7.7% peak-13.53pp-11.59pp-9.64pp1-7.70ppbin -7.70pp · n=1 · 7.7% peakbin -7.70pp · n=1 · 7.7% peak-5.75pp-3.81pp6-1.86ppbin -1.86pp · n=6 · 46.2% peakbin -1.86pp · n=6 · 46.2% peak130.08ppbin 0.08pp · n=13 · 100.0% peakbin 0.08pp · n=13 · 100.0% peak22.03ppbin 2.03pp · n=2 · 15.4% peakbin 2.03pp · n=2 · 15.4% peakμΔ < 0 · loss barsΔ ≈ 0 · flatΔ > 0 · gain barsN(μ,σ²) referenceμ line · ±σ band shaded
n=23
Q-Q plot · standardised Δp vs N(0,1)
n=23 · skew=-3.07 · kurt=9.69 · near 8 / mid 14 / far 1 · OLS slope=0.79 intercept=-0.00LEPTOKURTIC — FAT TAILSTHIN UPPER TAILLOWER TAIL NORMAL-3σ-3σ-2σ-2σ-1σ-1σ+0σ+0σ+1σ+1σ+2σ+2σ+3σ+3σΔ=-2.08σsample ↓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=24STRONGLY LEFT-SKEWED (G₁=-1.24)
μ MEAN18.68¢95% CI: [14.71¢, 22.65¢]
σ STD DEV9.93ppσ² = 98.615 · CV = 53.16%
med MEDIAN23.50¢Q₁ 20.25¢ · Q₃ 24.50¢
FIVE-NUMBER SUMMARY · BOX PLOTrange 26.45pp · IQR 4.25pp (1.349σ→13.40pp)
min 0.05¢Q₁ 20.25¢med 23.50¢Q₃ 24.50¢max 26.50¢μ
SKEWNESS · G₁-1.243left-skewed
−3−10+1+3
EXCESS KURTOSIS · G₂-0.346mesokurtic · normal-like
−30+2+4+6
μ ↔ medianμ < med · left-tailed|μ−med| / σ = 0.49
σ × 1.349 ↔ IQRdiverges from normalratio = 3.15
range ↔ σconcentrated (range < 4σ)range / σ = 2.66
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: TRENDING · variance ratio > 1
ρ(1) AUTOCORR+0.229within white-noise band
ρ(2) AUTOCORR-0.163lag-2 not significant
H · HURST EXPONENT1.064strongly persistent
OLS TREND · t-STAT-5.127significant @ α=0.05
HURST EXPONENT [0, 1]strongly persistent · H = 1.064
H = 1.064STRONGLY 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+0.229k=2-0.163k=3-0.002k=4-0.035k=5+0.0010+1−1+0.42−0.42+ momentum (ρ > +0.42)− reversal (ρ < −0.42)noise (within band)±2/√n threshold
OLS TREND · t-STAT · [-5, +5]SIGNIFICANT @ 1% (|t|=5.13)
−5 reject−1.960 retain H₀+1.96+5 reject
REGIME CLASSIFICATIONTRENDING · variance ratio > 1from Hurst + ρ(1) joint diagnosis
PREDICTABILITY · score 1.00very high · strong structure|ρ(1)| + 2·|H − 0.5| heuristic
TREND SIGNIFICANCESIGNIFICANT @ 1% (|t|=5.13)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 ID2276316
SLUGf1-catalunya-grand-prix-winner-antonelli-2026-06-14
CATEGORYSports
TWO-SIDED PRICINGFAVOURS NO (100¢)
PRIMARY · YES0.05¢implied prob 0.05% · decimal odds 2000.00×
COUNTER · NO99.95¢implied prob 99.95% · decimal odds 1.00×
0.05¢
99.95¢
Σ-SIDES ARBITRAGE TESTPERFECT · ARB-FREE Σ=100.00%
0%50%100% · target110%
Σ = 100.00% · |1 − Σ| = 0.000pp
24H ACTIVITY · LIQUIDITYDEEP
24H VOLUME140.30k USD 24h
LIQUIDITY30.02k USD
MARKET QUALITYPERFECT · ARB-FREE Σ=100.00%|1−Σ| ≤ 0.5pp ⇒ fair · > 2pp ⇒ inefficient
PRICING SKEWFAVOURS NO (100¢)|primary − counter| = 0.999 · entropy 0.006 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 0.1%NO 100.0%YES p̂0.1%H = 0.006 / 1.00 bits
Probability scale (YES)
0%25%50%
fair75%100%
Implied decimal odds
YES2000.00×(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) = 0.006 bits (1% 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 · LOWresolves 2026-06-21 13:00 UTC
6days
17hrs
48min
6.74 days·θ = 48.649 pp/day
YES →$1.00(P = 0.1%)
NO →$0.00(P = 100.0%)
current: $0.0005 · expected return per side: $1.00 on YES hit · $0.00 on NO hit
0%25%50%75%100%YES $1NO $0NOW+3.4dRESOLVESP projection · σ=9.93% · path funnel to settle at YES=1 or NO=0
Theta progression · θ ∝ σ / √t_remainingθ_now = 48.649 pp/day
now6.74d left
48.649 pp/day×1.00
−25%5.06d left
56.175 pp/day×1.15
−50%3.37d left
68.801 pp/day×1.41
−75%1.69d left
97.299 pp/day×2.00
−90%16.18h left
153.843 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=23 bars · best 3.00% · worst -16.45% · typical |Δ| 1.85%BEARISH SESSION -22.45%BEST+3.00%9hWORST-16.45%19hTYPICAL |Δ|1.85%mean absoluteCUMULATIVE-22.45%Σ signed ΔSTREAK▬ 0flat-runASIA · 00-08 UTCμ +0.07% · Σ +0.50%EUROPE · 08-16 UTCμ +0.06% · Σ +0.50%US · 16-24 UTCμ -2.93% · Σ -23.45%CUMULATIVE Δ PATH · final -22.45%+4.00%-22.45%1.00% · 1h1.00% · 1h1.00%1h1.00% · 2h1.00% · 2h1.00%2h-1.00% · 3h-1.00% · 3h-1.00%3h1.00% · 4h1.00% · 4h1.00%4h0.50% · 5h0.50% · 5h0.50%5h-0.50% · 6h-0.50% · 6h-0.50%6h-1.50% · 7h-1.50% · 7h-1.50%7h-0.50% · 8h-0.50% · 8h-0.50%8h3.00% · 9h3.00% · 9h3.00%9h★ BEST1.00% · 10h1.00% · 10h1.00%10h-1.00% · 11h-1.00% · 11h-1.00%11h-1.50% · 12h-1.50% · 12h-1.50%12h0.50% · 13h0.50% · 13h0.50%13h-1.00% · 14h-1.00% · 14h-1.00%14h0.00% · 15h0.00% · 15h·15h-2.00% · 16h-2.00% · 16h-2.00%16h2.00% · 17h2.00% · 17h2.00%17h-7.00% · 18h-7.00% · 18h-7.00%18h-16.45% · 19h-16.45% · 19h-16.45%19h▼ WORST0.00% · 20h0.00% · 20h·20h0.05% · 21h0.05% · 21h0.05%21h-0.05% · 22h-0.05% · 22h-0.05%22h0.00% · 23h0.00% · 23h·23hTIME PATTERNAsia-led (+0.50%)RUNSup max 2 · down max 3BREADTH39% up · 48% down · 13% flat
9 up bars · 11 down · best 3.00% · worst -16.45% · typical |Δ| 1.850%

§10 · Equity curve & underwater drawdown

Cumulative compounded return + running peak-to-trough
EQUITY & DRAWDOWN ANALYSIS · n=24 barsSEVERE DRAWDOWN -21.63%FINAL-21.63%MAX DD-24.64%RECOVERYONGOING · 13 barsMAX RUN-UP+3.99%UNDERWATER18/24 (75%)STREAK▬ 0EQUITY CURVE · end 0.7837 · peak 1.0399 · range [0.7837, 1.0399]1.03990.7837break-even = 1★ PEAK 1.0399UNDERWATER DRAWDOWN · max -24.64% · severe0%-24.64%▼ TROUGH -24.64%TOP DRAWDOWN PERIODS · 3 total#1 -24.64%bar 12-24 · 13 bars · ONGOING#2 -2.48%bar 7-9 · 3 bars · recovered#3 -1.00%bar 4-5 · 2 bars · recoveredDD SEVERITYsevere (max -24.64%)RECOVERYongoing · 13 barsTIME UNDER WATER75% of session · 18/24 bars
final equity 0.7837 (-21.63%) · max DD -24.64% · time-under-water 18/24 bars

§11 · Rolling-window statistics (w = 5 bars)

Rolling annualised Sharpe ratio · green positive · red negative
n=19 · +7 / −12 (37% positive) · μ=-21.22 · σ=37.49MIXED EDGELAST -41.86 (-0.55σ vs μ)72.2236.110.00-36.11-72.22μ = -21.2254.0454.0420.6120.61-27.08-27.08-19.21-19.2110.9010.9016.0116.0110.2710.2710.2710.2721.0121.01-34.54-34.54-68.35-68.35-72.22-72.22-6.17-6.17-44.55-44.55-59.51-59.51-59.51-59.51-52.60-52.60-60.64-60.64-41.86-41.86v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -41.856 · range [-72.22, 54.04] · μ -21.217 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
Rolling annualised volatility (%)
n=19 · μ=283.1009 · σ=256.7799 · range [76.8960, 712.8173] · R²=0.654▲ RISING +749.48%σ EXTREME 90.70%LAST 688.5539712.8173553.8370394.8567235.876376.8960μ = 283.1009max 712.8173min 76.8960dataMA(3)OLS R²=0.65μ lineμ ± σ bandmaxmin
latest 688.55% · range [76.90%, 712.82%] · μ 283.10% · σ̂ scaled to annualised (×√8760)
Rolling lag-1 autocorrelation ρ(1)
n=19 · +9 / −10 (47% positive) · μ=-0.120 · σ=0.306CLOSE TO MARTINGALELAST -0.050 (+0.23σ vs μ)0.5730.2860.000-0.286-0.573μ = -0.120-0.417-0.417-0.573-0.5730.0490.0490.3710.3710.0180.0180.2120.2120.0380.0380.1020.1020.2510.251-0.364-0.364-0.485-0.485-0.533-0.533-0.523-0.523-0.455-0.4550.1940.194-0.117-0.117-0.076-0.0760.0770.077-0.050-0.050v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -0.050 · |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
191.1234
p-VALUE (log scale)
< 0.0001
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
2.1340
p-VALUE (log scale)
0.8318
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
0.0572
p-VALUE (log scale)
0.9606
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
0.5108
p-VALUE (log scale)
0.6095
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedsigns appear random (12 runs)
χ

KPSS (μ stationarity)

REJECT H₀*

H₀: p IS level-stationary

STATISTIC
0.5788
p-VALUE (log scale)
0.0246
α
10⁻⁴10⁻³10⁻²10⁻¹1
p < α · rejection zonenon-stationary (crit 0.463)
χ

Variance ratio q=2

FAIL TO REJECTns

H₀: Δp is a random walk · VR = 1

STATISTIC
1.3367
p-VALUE (log scale)
0.1813
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedVR 1.279 ≈ 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=11 bins · noise floor μ=1.49e-3 · top T=3.83h (19.5%) · top-3 cover 49.0%1 SIGNIFICANT CYCLEcumulative energy ↗ (1 bin above 2× noise)3.2e-32.4e-31.6e-38.0e-40.0e+0μ noise floor2× noise (significance)period 23.0 · power 2.53e-3 · 15.4% energyperiod 23.0 · power 2.53e-3 · 15.4% energyperiod 11.5 · power 2.02e-3 · 12.4% energyperiod 11.5 · power 2.02e-3 · 12.4% energyperiod 7.7 · power 1.74e-3 · 10.6% energyperiod 7.7 · power 1.74e-3 · 10.6% energyperiod 5.8 · power 2.29e-3 · 14.0% energyperiod 5.8 · power 2.29e-3 · 14.0% energyperiod 4.6 · power 6.75e-4 · 4.1% energyperiod 4.6 · power 6.75e-4 · 4.1% energyperiod 3.8 · power 3.19e-3 · 19.5% energyperiod 3.8 · power 3.19e-3 · 19.5% energyperiod 3.3 · power 1.14e-3 · 6.9% energyperiod 3.3 · power 1.14e-3 · 6.9% energyperiod 2.9 · power 9.30e-4 · 5.7% energyperiod 2.9 · power 9.30e-4 · 5.7% energyperiod 2.6 · power 9.39e-4 · 5.7% energyperiod 2.6 · power 9.39e-4 · 5.7% energyperiod 2.3 · power 8.07e-4 · 4.9% energyperiod 2.3 · power 8.07e-4 · 4.9% energyperiod 2.1 · power 1.01e-4 · 0.6% energyperiod 2.1 · power 1.01e-4 · 0.6% energy50% by T=5.8h#1 dominantT=3.83h#2T=23.00h#3T=5.75hT=3hT=4hT=6hT=8hT=12hT=16h← 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 ≈ 3.83h (freq 0.261) · concentrates 19.5% of total energy · Σ|X̂|²/n = 1.636e-2

§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 6.7 d · σ/bar 3.856pp · expected |Δp| over horizon 49.06ppterminal variance p(1−p) = 0.0005 · n = 24⊘ disabled · n < 25
μ per bar
-0.976pp
average Δp · drift
σ per bar
3.856pp
one-bar volatility · logit-free
Per-day movedaily
18.89pp
σ × √24
Per-horizon move7d
49.06pp
σ × √161.81343083333334
Terminal variancebinary
0.0005
p(1−p) at resolution
Current pricep
0.1¢
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 7.32pp · ES₉₅ 8.93pp · method parametric · drift-correcteddrift -0.976pp/bar · quantised: yes · median step 0.50pp · unique ratio 0.50⊘ disabled · n < 30
VaR 95%
7.32pp
1.645·σ (parametric) of Δp
ES 95%
8.93pp
mean of the tail
Max drawdown
99.8pp
peak 26.5¢ → trough 0.1¢
Median step
0.50pp
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
0.1%
= price
Decimal oddsEU
2000.000
total return per $1
AmericanUS
+199900
$100 wins $199900
FractionalUK
1999.00 / 1
profit per $1 risked
Profit per $100stake
+$199900.00
clean dollar framing
-1000-5000+500+1000020406080100you · 0.1%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)
0.006 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.006 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
10.97 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
43187468984701261611389959172751806847869507855223825092913350551924777465230
NO token ID
111412919310526929597872143847320617409613937052036587442619928269607394998750
Snapshot fetched
2026-06-14 19:11:11 UTC
Snapshot age
6ms
History points
24 CLOB mids
Page rendered
2026-06-14 19:11:11 UTC
Storage policy
no persistence — fetched on every request
SHA-256 attestation
0bee2df902727a5f11ed17a49340830ceb7b12784188add6bba13e10f8d2413d · deterministic hash of source snapshot
Open data licence
CC0 / public domain

§∞-2 · Related markets · explore more

HL PREDGermany100.0¢HL PREDSpain89.5¢HL PREDUruguay66.9¢POLYMARKETWill Curaçao win on 2026-06-14?0¢POLYMARKETWill Australia win the 2026 FIFA World Cup?0¢POLYMARKETWill Scotland win the 2026 FIFA World Cup?0¢HL PERPBTC-USD perpetual$63,768.5HL PERPETH-USD perpetual$1,663.45HL PERPHYPE-USD perpetual$60.43

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
—
(best bid + best ask) / 2
Spread
—
(bestAsk − bestBid) / mid
Imbalance (whole book)
-1.000
ask-heavy
Imbalance (top-5)
-1.000
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-f1-catalunya-grand-prix-winner-antonelli-2026-06-14/slippage?size=10000&side=buy

SideNotionalAvg fillSlippageWorst fillLevelsStatus
BUY$1.00K————ERR
BUY$10.00K————ERR
BUY$100.00K————ERR
SELL$1.00K————ERR
SELL$10.00K————ERR
SELL$100.00K————ERR

Risk metrics

▸ upstream candles · 24 bars
Realized vol (annualised)
—
σ per bar = 1.227440
Mean return (annualised)
—
μ per bar = -0.265619
Sharpe (rf=0)
—
annualised; risk-free assumed zero
Max drawdown
99.81%
peak 0.27 → trough 0.00 over 9 bars

/api/asset/pm-f1-catalunya-grand-prix-winner-antonelli-2026-06-14/risk · same metrics, JSON