Weekly Lottery Intelligence Report
Week 17, 2026
This report consolidates structural monitoring across supported lotteries for the reporting period. Metrics are derived from rolling historical averages and variance windows. No predictive claims are made, and the analysis does not alter winning probabilities.
EuroMillions
Official Draw — 21 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 3-2 | Observed distribution alignment |
| High/Low | 2-3 | Range distribution relative to midpoint |
| Sum | 145 | Position within rolling variance band |
| Rolling Avg | 126.25 | 100-draw average reference |
| Std Dev | 26.570 | Historical dispersion window |
| Consecutive Pairs | 0 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Official Draw — 24 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 2-3 | Observed distribution alignment |
| High/Low | 1-4 | Range distribution relative to midpoint |
| Sum | 166 | Position within rolling variance band |
| Rolling Avg | 130.67 | 100-draw average reference |
| Std Dev | 28.350 | Historical dispersion window |
| Consecutive Pairs | 1 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
EuroMillions — Rolling 100-Draw Performance Snapshot
| Model | Avg Main Matches | ≥2 Match Rate |
|---|---|---|
| Statistical Model | 0.36 | 3.39% |
| Lotterics Adaptive | 0.35 | 3.51% |
Observed differences reflect historical distribution patterns and remain within stochastic variance bands.
Powerball
Official Draw — 20 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 3-2 | Observed distribution alignment |
| High/Low | 2-3 | Range distribution relative to midpoint |
| Sum | 173 | Position within rolling variance band |
| Rolling Avg | 179.92 | 100-draw average reference |
| Std Dev | 42.730 | Historical dispersion window |
| Consecutive Pairs | 0 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Official Draw — 22 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 3-2 | Observed distribution alignment |
| High/Low | 3-2 | Range distribution relative to midpoint |
| Sum | 197 | Position within rolling variance band |
| Rolling Avg | 178.33 | 100-draw average reference |
| Std Dev | 41.700 | Historical dispersion window |
| Consecutive Pairs | 0 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Official Draw — 25 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 1-4 | Observed distribution alignment |
| High/Low | 2-3 | Range distribution relative to midpoint |
| Sum | 179 | Position within rolling variance band |
| Rolling Avg | 174.00 | 100-draw average reference |
| Std Dev | 38.590 | Historical dispersion window |
| Consecutive Pairs | 0 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Powerball — Rolling 100-Draw Performance Snapshot
| Model | Avg Main Matches | ≥2 Match Rate |
|---|---|---|
| Statistical Model | 0.40 | 4.55% |
| Lotterics Adaptive | 0.38 | 3.7% |
Observed differences reflect historical distribution patterns and remain within stochastic variance bands.
Mega Millions
Official Draw — 21 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 2-3 | Observed distribution alignment |
| High/Low | 1-4 | Range distribution relative to midpoint |
| Sum | 194 | Position within rolling variance band |
| Rolling Avg | 184.08 | 100-draw average reference |
| Std Dev | 44.040 | Historical dispersion window |
| Consecutive Pairs | 0 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Official Draw — 24 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 2-3 | Observed distribution alignment |
| High/Low | 4-1 | Range distribution relative to midpoint |
| Sum | 130 | Position within rolling variance band |
| Rolling Avg | 181.92 | 100-draw average reference |
| Std Dev | 45.960 | Historical dispersion window |
| Consecutive Pairs | 0 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Mega Millions — Rolling 100-Draw Performance Snapshot
| Model | Avg Main Matches | ≥2 Match Rate |
|---|---|---|
| Statistical Model | 0.45 | 9.38% |
| Lotterics Adaptive | 0.39 | 6.45% |
Observed differences reflect historical distribution patterns and remain within stochastic variance bands.
Mega-Sena
Official Draw — 23 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 2-4 | Observed distribution alignment |
| High/Low | 3-3 | Range distribution relative to midpoint |
| Sum | 200 | Position within rolling variance band |
| Rolling Avg | 184.83 | 100-draw average reference |
| Std Dev | 27.440 | Historical dispersion window |
| Consecutive Pairs | 0 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Official Draw — 25 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 1-5 | Observed distribution alignment |
| High/Low | 2-4 | Range distribution relative to midpoint |
| Sum | 233 | Position within rolling variance band |
| Rolling Avg | 185.67 | 100-draw average reference |
| Std Dev | 28.710 | Historical dispersion window |
| Consecutive Pairs | 1 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Mega-Sena — Rolling 100-Draw Performance Snapshot
| Model | Avg Main Matches | ≥2 Match Rate |
|---|---|---|
| Statistical Model | 0.56 | 12.99% |
| Lotterics Adaptive | 0.69 | 16.0% |
Observed differences reflect historical distribution patterns and remain within stochastic variance bands.
Swiss Lotto
Official Draw — 22 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 2-4 | Observed distribution alignment |
| High/Low | 3-3 | Range distribution relative to midpoint |
| Sum | 132 | Position within rolling variance band |
| Rolling Avg | 127.67 | 100-draw average reference |
| Std Dev | 26.850 | Historical dispersion window |
| Consecutive Pairs | 0 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Official Draw — 25 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 4-2 | Observed distribution alignment |
| High/Low | 4-2 | Range distribution relative to midpoint |
| Sum | 110 | Position within rolling variance band |
| Rolling Avg | 127.50 | 100-draw average reference |
| Std Dev | 26.950 | Historical dispersion window |
| Consecutive Pairs | 1 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Swiss Lotto — Rolling 100-Draw Performance Snapshot
| Model | Avg Main Matches | ≥2 Match Rate |
|---|---|---|
| Statistical Model | 0.73 | 15.15% |
| Lotterics Adaptive | 0.68 | 18.46% |
Observed differences reflect historical distribution patterns and remain within stochastic variance bands.
SuperEnalotto
Official Draw — 21 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 3-3 | Observed distribution alignment |
| High/Low | 4-2 | Range distribution relative to midpoint |
| Sum | 253 | Position within rolling variance band |
| Rolling Avg | 237.50 | 100-draw average reference |
| Std Dev | 53.460 | Historical dispersion window |
| Consecutive Pairs | 1 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Official Draw — 23 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 1-5 | Observed distribution alignment |
| High/Low | 4-2 | Range distribution relative to midpoint |
| Sum | 219 | Position within rolling variance band |
| Rolling Avg | 239.25 | 100-draw average reference |
| Std Dev | 52.470 | Historical dispersion window |
| Consecutive Pairs | 0 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Official Draw — 24 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 3-3 | Observed distribution alignment |
| High/Low | 4-2 | Range distribution relative to midpoint |
| Sum | 239 | Position within rolling variance band |
| Rolling Avg | 231.25 | 100-draw average reference |
| Std Dev | 43.880 | Historical dispersion window |
| Consecutive Pairs | 0 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
SuperEnalotto — Rolling 100-Draw Performance Snapshot
| Model | Avg Main Matches | ≥2 Match Rate |
|---|---|---|
| Statistical Model | 0.41 | 9.47% |
| Lotterics Adaptive | 0.42 | 5.38% |
Observed differences reflect historical distribution patterns and remain within stochastic variance bands.
La Primitiva
Official Draw — 20 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 4-2 | Observed distribution alignment |
| High/Low | 2-4 | Range distribution relative to midpoint |
| Sum | 168 | Position within rolling variance band |
| Rolling Avg | 163.50 | 100-draw average reference |
| Std Dev | 30.660 | Historical dispersion window |
| Consecutive Pairs | 0 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Official Draw — 23 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 3-3 | Observed distribution alignment |
| High/Low | 3-3 | Range distribution relative to midpoint |
| Sum | 131 | Position within rolling variance band |
| Rolling Avg | 160.17 | 100-draw average reference |
| Std Dev | 31.810 | Historical dispersion window |
| Consecutive Pairs | 1 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Official Draw — 25 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 1-5 | Observed distribution alignment |
| High/Low | 3-3 | Range distribution relative to midpoint |
| Sum | 123 | Position within rolling variance band |
| Rolling Avg | 156.67 | 100-draw average reference |
| Std Dev | 33.360 | Historical dispersion window |
| Consecutive Pairs | 0 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
La Primitiva — Rolling 100-Draw Performance Snapshot
| Model | Avg Main Matches | ≥2 Match Rate |
|---|---|---|
| Statistical Model | 0.55 | 5.75% |
| Lotterics Adaptive | 0.62 | 12.79% |
Observed differences reflect historical distribution patterns and remain within stochastic variance bands.
EuroDreams
Official Draw — 20 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 4-2 | Observed distribution alignment |
| High/Low | 3-3 | Range distribution relative to midpoint |
| Sum | 108 | Position within rolling variance band |
| Rolling Avg | 120.50 | 100-draw average reference |
| Std Dev | 29.400 | Historical dispersion window |
| Consecutive Pairs | 0 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Official Draw — 23 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 5-1 | Observed distribution alignment |
| High/Low | 3-3 | Range distribution relative to midpoint |
| Sum | 103 | Position within rolling variance band |
| Rolling Avg | 118.67 | 100-draw average reference |
| Std Dev | 29.740 | Historical dispersion window |
| Consecutive Pairs | 1 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
EuroDreams — Rolling 100-Draw Performance Snapshot
| Model | Avg Main Matches | ≥2 Match Rate |
|---|---|---|
| Statistical Model | 0.96 | 25.0% |
| Lotterics Adaptive | 0.95 | 23.64% |
Observed differences reflect historical distribution patterns and remain within stochastic variance bands.
UK Lotto
Official Draw — 22 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 2-4 | Observed distribution alignment |
| High/Low | 4-2 | Range distribution relative to midpoint |
| Sum | 170 | Position within rolling variance band |
| Rolling Avg | 178.67 | 100-draw average reference |
| Std Dev | 47.840 | Historical dispersion window |
| Consecutive Pairs | 0 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Official Draw — 25 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 3-3 | Observed distribution alignment |
| High/Low | 4-2 | Range distribution relative to midpoint |
| Sum | 131 | Position within rolling variance band |
| Rolling Avg | 171.00 | 100-draw average reference |
| Std Dev | 47.490 | Historical dispersion window |
| Consecutive Pairs | 0 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
UK Lotto — Rolling 100-Draw Performance Snapshot
| Model | Avg Main Matches | ≥2 Match Rate |
|---|---|---|
| Statistical Model | 0.68 | 10.53% |
| Lotterics Adaptive | 0.77 | 17.31% |
Observed differences reflect historical distribution patterns and remain within stochastic variance bands.
German Lotto 6aus49
Official Draw — 22 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 4-2 | Observed distribution alignment |
| High/Low | 1-5 | Range distribution relative to midpoint |
| Sum | 192 | Position within rolling variance band |
| Rolling Avg | 158.67 | 100-draw average reference |
| Std Dev | 31.260 | Historical dispersion window |
| Consecutive Pairs | 1 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Official Draw — 25 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 3-3 | Observed distribution alignment |
| High/Low | 4-2 | Range distribution relative to midpoint |
| Sum | 137 | Position within rolling variance band |
| Rolling Avg | 157.75 | 100-draw average reference |
| Std Dev | 31.720 | Historical dispersion window |
| Consecutive Pairs | 0 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
German Lotto 6aus49 — Rolling 100-Draw Performance Snapshot
| Model | Avg Main Matches | ≥2 Match Rate |
|---|---|---|
| Statistical Model | 0.56 | 12.5% |
| Lotterics Adaptive | 0.72 | 15.22% |
Observed differences reflect historical distribution patterns and remain within stochastic variance bands.
Irish Lotto
Official Draw — 22 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 3-3 | Observed distribution alignment |
| High/Low | 5-1 | Range distribution relative to midpoint |
| Sum | 95 | Position within rolling variance band |
| Rolling Avg | 141.25 | 100-draw average reference |
| Std Dev | 36.850 | Historical dispersion window |
| Consecutive Pairs | 1 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Official Draw — 25 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 4-2 | Observed distribution alignment |
| High/Low | 2-4 | Range distribution relative to midpoint |
| Sum | 164 | Position within rolling variance band |
| Rolling Avg | 141.25 | 100-draw average reference |
| Std Dev | 36.850 | Historical dispersion window |
| Consecutive Pairs | 2 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Irish Lotto — Rolling 100-Draw Performance Snapshot
| Model | Avg Main Matches | ≥2 Match Rate |
|---|---|---|
| Statistical Model | 0.40 | 6.67% |
| Lotterics Adaptive | 0.51 | 11.63% |
Observed differences reflect historical distribution patterns and remain within stochastic variance bands.
Australian Lotto
Official Draw — 25 April 2026
Official Numbers
Structural Pattern Analysis
| Metric | Value | Statistical Context |
|---|---|---|
| Odd/Even | 4-2 | Observed distribution alignment |
| High/Low | 5-1 | Range distribution relative to midpoint |
| Sum | 102 | Position within rolling variance band |
| Rolling Avg | 128.83 | 100-draw average reference |
| Std Dev | 35.620 | Historical dispersion window |
| Consecutive Pairs | 1 | Observed adjacency frequency |
Model Performance Comparison
| Model | Prediction | Main Matches |
|---|---|---|
| Statistical Model | — | 0 |
| Lotterics Adaptive | — | 0 |
| Best Weekly Match Level | 0 |
Australian Lotto — Rolling 100-Draw Performance Snapshot
| Model | Avg Main Matches | ≥2 Match Rate |
|---|---|---|
| Statistical Model | 0.48 | 8.7% |
| Lotterics Adaptive | 0.41 | 13.64% |
Observed differences reflect historical distribution patterns and remain within stochastic variance bands.