POLYMARKET · PREDICTION MARKET · SPORTS
Will Mexico win the 2026 FIFA World Cup?
1.3¢
98.8¢
▸ Advanced metrics · M2M bundle
polymarket · will-mexico-win-the-2026-fifa-world-cup-529 · fresh · feed 7s old24h sparkline · 60 pts▼ —
realized vol (ann.)
2.96%
max drawdown
7.41%
sharpe
—
ulcer index
4.00%
RMS drawdown
pain index
2.16%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
7.41%
cond. drawdown
gain/pain
0.00
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
0.00
upside/downside
roll spread
0.8 bps
implied (price-only)
bars used
2000
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API:
/api/m2m/pm-will-mexico-win-the-2026-fifa-world-cup-529/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
1.3¢
NO · live
98.8¢
25 ticks · last 1.25¢
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.097 / 1.00 bits (10%) · informative — one side favoured
YES1.3%1.3¢80.00×▬ +0.00pp
NO98.8%98.8¢1.01×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Σ 20bp moved · peak 10bp · n=24 ticks
7.0s
1.25¢ (1.25%)
98.75¢ (98.75%)
100.00%
0.000pp
$2.2M
$2.9M
25 ticks (live)
§1 · 24h price history (YES + NO tokens)
25 YES observations from clob.polymarket.com · last 1.25¢
25 NO observations from clob.polymarket.com · last 98.75¢
§2 · Distribution of Δp
n=24
reference line = identity (perfect normality). Heavy upper-right tail = fat positive tail.
§3 · Sample moments
SAMPLE MOMENTS · N=25APPROXIMATELY NORMAL · WELL-BEHAVED
FIVE-NUMBER SUMMARY · BOX PLOT
SKEWNESS · G₁-0.195approximately symmetric
−3−10+1+3
EXCESS KURTOSIS · G₂0.775mesokurtic · 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: MEAN-REVERTING · ADF rejects unit root
HURST EXPONENT [0, 1]
H = 0.977STRONGLY 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
1.25¢
98.75¢
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
YES80.00×(1¢)NO1.01×(99¢)
Kelly bet-size (% of bankroll) K* = 0.00%
Entropy H(p̂) = 0.097 bits (10% of max) · informative — one side strongly favoured
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 · DISTANTresolves 2026-07-20 00:00 UTC
35days
14hrs
11min
YES →$1.00
NO →$0.00
current: $0.0125 · expected return per side: $0.99 on YES hit · $0.01 on NO hit
Theta progression · θ ∝ σ / √t_remainingθ_now = 0.242 pp/day
now35.59d left0.242 pp/day×1.00
−25%26.69d left0.279 pp/day×1.15
−50%17.80d left0.342 pp/day×1.41
−75%8.90d left0.483 pp/day×2.00
−90%3.56d left0.764 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
0 up bars · 2 down · best 0.00% · worst -0.10% · typical |Δ| 0.008%
§10 · Equity curve & underwater drawdown
final equity 0.9980 (-0.20%) · max DD -0.20% · time-under-water 23/25 bars
§11 · Rolling-window statistics (w = 6 bars)
latest -38.210 · range [-38.21, 0.00] · μ -12.066 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
latest 3.82% · range [0.00%, 3.82%] · μ 1.21% · σ̂ scaled to annualised (×√8760)
latest -0.233 · |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 5 REJECT · mixed evidence2 reject·3 pass·1 n/a·α = 0.05
Jarque-Bera
REJECT H₀***H₀: Δp ~ Normal(μ, σ²)
STATISTIC
124.7193
p-VALUE (log scale)
< 0.0001
Ljung-Box(h=5)
FAIL TO REJECTnsH₀: No serial autocorrelation up to lag 5
STATISTIC
0.4379
p-VALUE (log scale)
0.9924
Dickey-Fuller (τ_μ)
FAIL TO REJECTnsH₀: p has a unit root (non-stationary)
STATISTIC
-1.8059
p-VALUE (log scale)
0.3876
Wald-Wolfowitz runs
N/An/aH₀: Sign sequence of Δ is random
STATISTIC
—
p-VALUE (log scale)
—
KPSS (μ stationarity)
REJECT H₀*H₀: p IS level-stationary
STATISTIC
0.6173
p-VALUE (log scale)
0.0211
Variance ratio q=3
FAIL TO REJECTnsH₀: Δp is a random walk · VR = 1
STATISTIC
-0.7579
p-VALUE (log scale)
0.4485
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 ≈ 4.80h (freq 0.208) · concentrates 17.9% of total energy · Σ|X̂|²/n = 9.167e-7
▸ Depth section using sovereign-store price series (2562 bars · effective 1752810 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 35.6 d · σ/bar 0.002pp · expected |Δp| over horizon 0.06ppterminal variance p(1−p) = 0.0123 · n = 2562✓ n = 2562
μ per bar
-0.000pp
average Δp · drift
σ per bar
0.002pp
one-bar volatility · logit-free
Per-day movedaily
0.01pp
σ × √24
Per-horizon move36d
0.06pp
σ × √854.1909633333332
Terminal variancebinary
0.0123
p(1−p) at resolution
Current pricep
1.3¢
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
VaR₉₅ 0.00pp · ES₉₅ 0.00pp · method parametric · drift-correcteddrift -0.000pp/bar · quantised: yes · median step 0.10pp · unique ratio 0.00✓ n = 2562
VaR 95%
0.00pp
1.645·σ (parametric) of Δp
ES 95%
0.00pp
mean of the tail
Max drawdown
7.4pp
peak 1.4¢ → trough 1.3¢
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
Implied probabilityP
1.3%
= price
Decimal oddsEU
80.000
total return per $1
AmericanUS
+7900
$100 wins $7900
FractionalUK
79.00 / 1
profit per $1 risked
Profit per $100stake
+$7900.00
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)
0.097 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.097 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
6.32 bit
self-information
Surprise · NO−log₂(1−p)
0.02 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
22587775301869146748237913050505932485648958481571808324285560650057390882036- NO token ID
89041006475364789358805026139650677807087698981377208157664917554760333198878- Snapshot fetched
- 2026-06-14 09:48:25 UTC
- Snapshot age
- 7.0s
- History points
- 25 CLOB mids
- Page rendered
- 2026-06-14 09:48:32 UTC
- Storage policy
- no persistence — fetched on every request
- SHA-256 attestation
d7b913b33de83a452d3a4de08bb0c81b854b50e0be8d5e9af8ce4aa91435eaee· deterministic hash of source snapshot- Open data licence
- CC0 / public domain
§∞-2 · Related markets · explore more
HL PREDGermany94.4¢HL PREDSpain90.3¢HL PREDUruguay67.7¢POLYMARKETWill Australia win the 2026 FIFA World Cup?0¢POLYMARKETWill Scotland win the 2026 FIFA World Cup?0¢POLYMARKETUS x Iran permanent peace deal by June 15, 2026?24¢HL PERPBTC-USD perpetual$64,546HL PERPETH-USD perpetual$1,677HL PERPHYPE-USD perpetual$60.48
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
0.012500
(best bid + best ask) / 2
Spread
800.0bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
-0.363
ask-heavy
Imbalance (top-5)
+0.626
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-mexico-win-the-2026-fifa-world-cup-529/slippage?size=10000&side=buy
| Side | Notional | Avg fill | Slippage | Worst fill | Levels | Status |
|---|---|---|---|---|---|---|
| BUY | $1.00K | 0.013000 | 400.00bp | 0.013000 | 1 | FILLED |
| BUY | $10.00K | 0.013224 | 579.32bp | 0.014000 | 2 | FILLED |
| BUY | $100.00K | 0.037730 | 20184.38bp | 0.489000 | 139 | FILLED |
| SELL | $1.00K | 0.012000 | 400.00bp | 0.012000 | 1 | FILLED |
| SELL | $10.00K | 0.012000 | 400.00bp | 0.012000 | 1 | FILLED |
| SELL | $100.00K | 0.005921 | 5263.31bp | 0.001000 | 12 | PARTIAL |
Risk metrics
▸ sovereign store · 2,562 barsperiods/year ≈ 1.75MRealized vol (annualised)
201.34%
σ per bar = 0.001521
Mean return (annualised)
-5267.40%
μ per bar = -0.000030
Sharpe (rf=0)
-26.16
annualised; risk-free assumed zero
Max drawdown
7.41%
peak 0.01 → trough 0.01 over 1980 bars
/api/asset/pm-will-mexico-win-the-2026-fifa-world-cup-529/risk · same metrics, JSON