Project Description
Complete Lottery Prediction and Betting Automation System (Focused on Loterías y Apuestas del Estado - Spain)
2. System Features
2.1. Historical Data Collection and Update
The system must automatically download complete historical results (drawn numbers, draw dates, prize breakdowns by category, accumulated jackpots) from the first draw of each lottery, directly from loteriasyapuestas.es or reliable associated sources.
Specific sources:
Euromillones: loteriasyapuestas.es/es/euromillones (since Feb 13, 2004)
La Primitiva: loteriasyapuestas.es/es/la-primitiva (since Oct 17, 1985 – modern version)
El Gordo de la Primitiva: loteriasyapuestas.es/es/gordo-primitiva (since Oct 31, 1993)
Updates automatic at exactly 00:02 the day after each draw, using ethical scraping (BeautifulSoup/Scrapy) with proper user-agent headers to mimic human behavior.
Store data in PostgreSQL (structured) or MongoDB (flexible), including all prize categories to enable ROI calculations and backtesting.
2.2. Number Prediction
Generate predictions for Euromillones, La Primitiva and/or El Gordo simultaneously using explicit advanced AI models:
Machine Learning ensembles (Random Forests) for frequency/statistical patterns
Deep Learning RNN/LSTM for time-series analysis and sequential trends
Neuro-Symbolic AI to combine logical rules with neural learning
Evolutionary/Genetic Algorithms to evolve optimal combinations
Bayesian Networks for conditional probabilities between numbers
Analyze full history (numbers, frequencies, temporal patterns, prizes, jackpots) and incorporate:
Hot/cold number analysis
Wheeling systems for guaranteed coverage of partial prizes
Monte Carlo simulations to estimate expected value (EV) for high jackpots
Generate blocks of 10 bets at a time using itertools for diversity.
User selects total bets (predefined: 10, 20, 50, 100, 500, 1,000, 5,000 or custom), with AI suggestions based on current jackpot (daily scraped), historical odds and bankroll.
After each real draw: compare results, report additional bets needed to hit jackpot (what-if simulations with genetic algorithms), and detail prizes won (hypothetical or actual).
Full backtesting: simulate from first historical draw, calculate bets required to cover winner (dynamic, no fixed limit – supports thousands/millions hypothetical bets), using Evolutionary Algorithms; report hit rates, average hypothetical ROI, patterns via LSTM/Bayesian.
2.3. Flexible Draw Days
Allow manual/automatic changes to draw days (official changes/holidays), stored dynamically in DB.
Interactive calendar (FullCalendar) with email/SMS alerts and real-time scraping for schedule updates.
2.4. Bet Cost Calculation
Auto-calculate total cost based on user-selected bets (blocks of 10+), fixed prices:
Euromillones: €2.50
La Primitiva: €1.00
El Gordo: €1.50
Dynamic AI suggestions: recommend bet quantity based on backtesting, current jackpot and balance, using Monte Carlo for EV (prioritize positive EV scenarios).
2.5. Login and Bet Execution Automation
Never store login/password (not even encrypted). Prompt user for credentials (email/NIF/NIE + password) every login, using secure masked fields.
Login process: Selenium (headless Chrome/Firefox), access https://juegos.loteriasyapuestas.es/jugar/login, fill form, submit, verify success (post-login elements), handle sessions/cookies.
Bet execution: navigate to lottery page, generate AI numbers, add exact user-requested bets to cart (batches for high volumes), support rules of each lottery.
Finalization: show full summary (lottery, bets, cost, numbers); require explicit user confirmation before submitting (“Confirm and Submit Bets”).
Payment handling: scrape Lotobolsa balance post-login; if insufficient, pause, notify user exact top-up amount via registered bank account (BBVA/CaixaBank transfer, min €1), wait for manual confirmation or recheck; proceed only on sufficient balance + user confirmation. Capture receipt, notify user, log details (no credentials).
Security: random delays, CAPTCHA handling (user intervention), geoblock alerts, expired session relogin, respect site limits. All via Selenium (no public API).
2.6. Simulations and Reports
Historical backtesting: complete simulations from first draw, report per draw: bets needed to cover jackpot (dynamic via Evolutionary Algorithms), hypothetical prizes, metrics (hit rate, ROI, patterns via LSTM/Bayesian).
Post-draw reports: actual matches, minimum bets to win, next-cycle suggestions.
User options: custom simulations, bet quantity definition, PDF/Excel export with charts.
2.7. User Interface
Prediction screen: numbers in blocks of 10, probabilities, wheeling suggestions, bet adjustment
Betting screen: lottery selection, bet input, cost & EV simulations, start button
Login/Config: credential fields (each use), login test, bankroll
Confirmation screen: summary + mandatory user confirmation
Agenda: interactive calendar with alerts
Backtesting: graphical reports (Matplotlib/Plotly) – frequencies, performance, ROI
Responsive design, intuitive dashboards (heatmaps, multi-lottery support).
3. Detailed Implementation
3.1. Data Structure: DB schemas for lotteries (rules/ranges/draw days), full history (indexed), user settings (no credentials).
3.2. Draw Day Changes: internal API with official validation & calendar sync.
3.3. Cost Calculation: dynamic Python functions + jackpot scraping & EV.
3.4. Prediction: train RNN/LSTM (PyTorch/TensorFlow), combinatorial generation (itertools), Genetic optimization.
3.5. Backtesting: parallel scripts (multiprocessing), no bet limits, model cross-validation.
3.6. Automation: as in 2.5, with execution logs and real-time UI feedback.
4. Conclusion
System developed for exclusive personal use, integrating data collection, multi-model AI optimization, supervised secure automation with user confirmations, and comprehensive reporting.