Double Color Ball Predictor
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About this skill
What It Solves
Double Color Ball draws are independent random events. This skill treats “prediction” as historical pattern analysis rather than guaranteed hitting. It helps quickly inspect omissions, hot/cold numbers, sum values, odd-even ratios, and zone distribution, then generate a few reasoned reference number sets.
How It Works
It supports two modes: when Python is unavailable, the agent follows the documented heuristics; when Python is available, commands such as scripts/ssq_predictor.py predict generate number sets, while fetch, backtest, and stats refresh data/history.json, evaluate past periods, and show statistical breakdowns. The v2.2 behavior also checks cache freshness and limits red-number overlap across generated sets, reducing near-duplicate outputs.
Key analysis dimensions include:
- Frequency and omission: historical occurrence counts and periods since last appearance
- Structural constraints: sum, odd/even, high/low, consecutive pairs, span, and AC value
- Combination strategies: balanced, cold-number recovery, and hot-number tracking
- Result reconciliation: latest checks official draw results, while evaluate reports prize-level distribution
Boundaries
This tool is for mathematical study, statistical learning, and entertainment only. Model weights can be iterated from backtests and prediction records, but past performance does not imply future results; no model can truly predict independent random draws, and the output is not betting advice.
Use Cases
- Compute red and blue frequency and top-10 omissions over the last 200 draws, then summarize zone distribution.
- Run a 50-draw backtest to check whether prize-level hits stay stable across the prediction strategy.
- Without Python, generate three reference number sets using hot/cold rules and sum-value constraints.
- Analyze one given red/blue combination for odd/even balance, span, and AC value sanity.
Best For
- Graduate students teaching probability who want to demo frequency, omission, and structural-constraint analysis on lottery history.
- Data-analysis engineers who need to turn official API feeds or local caches into a reproducible backtesting pipeline.
- Lottery-rule enthusiasts who want to compare combinations by odd/even ratio, sum, span, and AC value.
- Agent developers who need the assistant to produce structured statistical conclusions even without a Python runtime.
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