POLYMARKET · PREDICTION MARKET · SPORTS
Will Brazil win Group C in the 2026 FIFA World Cup?
59.5¢
40.5¢
▸ Advanced metrics · M2M bundle
polymarket · will-brazil-win-group-c-in-the-2026-fifa-world-cup · fresh · feed 0s old24h sparkline · 60 pts▼ -14.39%
realized vol (ann.)
29.60%
max drawdown
1.65%
sharpe
—
ulcer index
1.48%
RMS drawdown
pain index
1.32%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
1.65%
cond. drawdown
gain/pain
0.00
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
0.00
upside/downside
roll spread
0.2 bps
implied (price-only)
bars used
2000
store
spread
—
24h Δ
-14.39%
flow lean
—
carry
flat
signalNEUTRALconfidence 25%
- 24h change -14.39%
Same bundle via M2M API:
/api/m2m/pm-will-brazil-win-group-c-in-the-2026-fifa-world-cup/bundle · venue execution: polymarket →LIVEPOLL0SRCFRESH⏱--:--:-- UTCNEXT8.0sUP0s--:--HIST
▶ 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
59.5¢
NO · live
40.5¢
25 ticks · last 59.50¢
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.974 / 1.00 bits (97%) · max uncertainty (~50/50)
YES59.5%59.5¢1.68×▬ +0.00pp
NO40.5%40.5¢2.47×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Σ 1500bp moved · peak 800bp · n=24 ticks
6ms
59.50¢ (59.50%)
40.50¢ (40.50%)
100.00%
0.000pp
$44.8k
$61.2k
25 ticks (live)
§1 · 24h price history (YES + NO tokens)
25 YES observations from clob.polymarket.com · last 59.50¢
25 NO observations from clob.polymarket.com · last 40.50¢
§2 · Distribution of Δp
n=24
reference line = identity (perfect normality). Heavy upper-right tail = fat positive tail.
§3 · Sample moments
SAMPLE MOMENTS · N=25STRONGLY RIGHT-SKEWED (G₁=1.09)
FIVE-NUMBER SUMMARY · BOX PLOT
SKEWNESS · G₁1.091right-skewed
−3−10+1+3
EXCESS KURTOSIS · G₂-0.713mesokurtic · normal-like
−30+2+4+6
μ = mean YES probability · σ = standard deviation · 95% CI = μ ± 1.96·SE. Skew/kurt diagnose departure from normality.
§5 · Time-series structure
TIME-SERIES STRUCTUREREGIME: INDETERMINATE · weak signal at n=24
HURST EXPONENT [0, 1]
H = 1.203STRONGLY PERSISTENT
0
anti-persistent0.45
mean-reverting0.5
random walk0.55
persistent1
strongly trending
anti-persistent0.45
mean-reverting0.5
random walk0.55
persistent1
strongly trending
AUTOCORRELATION FUNCTION · ρ(k) for k=1..5
OLS TREND · t-STAT · [-5, +5]
−5 reject−1.960 retain H₀+1.96+5 reject
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
MICROSTRUCTURE · MARKET QUALITYPERFECT · ARB-FREE Σ=100.00%
TWO-SIDED PRICING
59.50¢
40.50¢
Σ-SIDES ARBITRAGE TEST
Σ = 100.00% · |1 − Σ| = 0.000pp
24H ACTIVITY · LIQUIDITY
Σ-sides = YES + NO implied probabilities. Perfect arb-free Σ = 100%. |1−Σ| > 2pp suggests synthetic outright arbitrage.
§7 · Position sizing & edge analysis
FAIR MARKET · no edge
Probability scale (YES)
Implied decimal odds
YES1.68×(60¢)NO2.47×(41¢)
Kelly bet-size (% of bankroll) K* = -0.00%
Entropy H(p̂) = 0.974 bits (97% of max) · maximum uncertainty (~50/50)
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
⏱ URGENCY · LOWresolves 2026-06-27 00:00 UTC
12days
07hrs
43min
YES →$1.00
NO →$0.00
current: $0.5950 · expected return per side: $0.41 on YES hit · $0.59 on NO hit
Theta progression · θ ∝ σ / √t_remainingθ_now = 23.888 pp/day
now12.32d left23.888 pp/day×1.00
−25%9.24d left27.584 pp/day×1.15
−50%6.16d left33.783 pp/day×1.41
−75%3.08d left47.776 pp/day×2.00
−90%1.23d left75.541 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
2 up bars · 5 down · best 1.00% · worst -8.00% · typical |Δ| 0.625%
§10 · Equity curve & underwater drawdown
final equity 0.8835 (-11.65%) · max DD -12.09% · time-under-water 22/25 bars
§11 · Rolling-window statistics (w = 6 bars)
latest 0.000 · range [-52.79, 0.00] · μ -30.990 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
latest 0.00% · range [0.00%, 311.83%] · μ 122.15% · σ̂ scaled to annualised (×√8760)
latest 0.000 · |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)
2 of 6 REJECT · mixed evidence2 reject·4 pass·α = 0.05
Jarque-Bera
REJECT H₀***H₀: Δp ~ Normal(μ, σ²)
STATISTIC
343.5480
p-VALUE (log scale)
< 0.0001
Ljung-Box(h=5)
FAIL TO REJECTnsH₀: No serial autocorrelation up to lag 5
STATISTIC
2.7781
p-VALUE (log scale)
0.7366
Dickey-Fuller (τ_μ)
FAIL TO REJECTnsH₀: p has a unit root (non-stationary)
STATISTIC
-1.7097
p-VALUE (log scale)
0.4335
Wald-Wolfowitz runs
FAIL TO REJECTnsH₀: Sign sequence of Δ is random
STATISTIC
0.1519
p-VALUE (log scale)
0.8793
KPSS (μ stationarity)
REJECT H₀*H₀: p IS level-stationary
STATISTIC
0.6966
p-VALUE (log scale)
0.0139
Variance ratio q=3
FAIL TO REJECTnsH₀: Δp is a random walk · VR = 1
STATISTIC
0.2813
p-VALUE (log scale)
0.7785
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)
dominant period ≈ 3.43h (freq 0.292) · concentrates 14.7% of total energy · Σ|X̂|²/n = 3.444e-3
▸ Depth section using sovereign-store price series (3622 bars · effective 1752908 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
Horizon 12.3 d · σ/bar 0.283pp · expected |Δp| over horizon 4.87ppterminal variance p(1−p) = 0.2410 · n = 3622✓ n = 3622
μ per bar
-0.003pp
average Δp · drift
σ per bar
0.283pp
one-bar volatility · logit-free
Per-day movedaily
1.39pp
σ × √24
Per-horizon move12d
4.87pp
σ × √295.7234702777778
Terminal variancebinary
0.2410
p(1−p) at resolution
Current pricep
59.5¢
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
VaR₉₅ 0.47pp · ES₉₅ 0.59pp · method parametric · drift-correcteddrift -0.003pp/bar · quantised: yes · median step 1.00pp · unique ratio 0.00✓ n = 3622
VaR 95%
0.47pp
1.645·σ (parametric) of Δp
ES 95%
0.59pp
mean of the tail
Max drawdown
23.7pp
peak 69.5¢ → trough 53.0¢
Median step
1.00pp
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
Implied probabilityP
59.5%
= price
Decimal oddsEU
1.681
total return per $1
AmericanUS
-147
risk $147 to win $100
FractionalUK
0.68 / 1
profit per $1 risked
Profit per $100stake
+$68.07
clean dollar framing
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
Market entropyH(p)
0.974 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.974 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
0.75 bit
self-information
Surprise · NO−log₂(1−p)
1.30 bit
self-information
Market entropy only — model entropy requires an external q.
§19 · Model-dependent surfaces
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
81847767762276015376638362563472043266790475968888863771265036582040507866830- NO token ID
284717320081839269860357237903286904886607070475454682161945348414652316634- Snapshot fetched
- 2026-06-14 16:16:35 UTC
- Snapshot age
- 6ms
- History points
- 25 CLOB mids
- Page rendered
- 2026-06-14 16:16:35 UTC
- Storage policy
- no persistence — fetched on every request
- SHA-256 attestation
6ba071a716be8ebccebbd222591f6b66b37b1988550b365169397db77bd45f85· deterministic hash of source snapshot- Open data licence
- CC0 / public domain
§∞-2 · Related markets · explore more
HL PREDGermany94.2¢HL PREDSpain89.6¢HL PREDUruguay66.9¢POLYMARKETWill Australia win the 2026 FIFA World Cup?0¢POLYMARKETWill Scotland win the 2026 FIFA World Cup?0¢POLYMARKETWill Turkiye win the 2026 FIFA World Cup?1¢HL PERPBTC-USD perpetual$64,093.5HL PERPETH-USD perpetual$1,664.45HL PERPHYPE-USD perpetual$60.32
Also see: /arb opportunities · RSS feed · more in Sports
Market depth
▸ live order book · Polymarket YESDepth 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
0.595000
(best bid + best ask) / 2
Spread
168.1bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
+0.247
bid-heavy
Imbalance (top-5)
+0.432
bid-heavy top-of-book
Slippage scenarios
▸ live book walk · Polymarket YESSimulating 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-brazil-win-group-c-in-the-2026-fifa-world-cup/slippage?size=10000&side=buy
| Side | Notional | Avg fill | Slippage | Worst fill | Levels | Status |
|---|---|---|---|---|---|---|
| BUY | $1.00K | 0.604482 | 159.35bp | 0.610000 | 2 | FILLED |
| BUY | $10.00K | 0.614808 | 332.91bp | 0.630000 | 4 | FILLED |
| BUY | $100.00K | 0.698245 | 1735.21bp | 0.990000 | 32 | PARTIAL |
| SELL | $1.00K | 0.588970 | 101.35bp | 0.580000 | 2 | FILLED |
| SELL | $10.00K | 0.576112 | 317.45bp | 0.570000 | 3 | FILLED |
| SELL | $100.00K | 0.496901 | 1648.72bp | 0.010000 | 15 | PARTIAL |
Risk metrics
▸ sovereign store · 3,622 barsperiods/year ≈ 1.75MRealized vol (annualised)
623.88%
σ per bar = 0.004712
Mean return (annualised)
-7520.44%
μ per bar = -0.000043
Sharpe (rf=0)
-12.05
annualised; risk-free assumed zero
Max drawdown
23.74%
peak 0.69 → trough 0.53 over 117 bars
/api/asset/pm-will-brazil-win-group-c-in-the-2026-fifa-world-cup/risk · same metrics, JSON