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Quantitative Tennis Betting Bot – Technical & Model Audit

Бюджет: - HOURLY / PART_TIME ⭐ 0.00 (0) Spain

python, django-framework, data-extraction, scrapy-framework, selenium, browser-automation, automation, api-integration, api-development, database-development, postgresql, docker

Preferred qualifications

  • Experience: Intermediate
I am developing a quantitative tennis betting system and am looking for an initial paid technical and quantitative audit of the existing project before considering a larger development engagement. The system is already under development and currently includes: - historical tennis data pipelines; - Elo-based features; - probability modelling and calibration; - sportsbook odds ingestion and matching; - walk-forward testing and backtesting; - prospective odds capture; - bet tracking and research-focused validation. The objective is not to build a generic odds scraper or high-volume betting bot. I want to determine whether the current approach can estimate probabilities independently from the market and identify a relatively small number of strong positive-EV opportunities. I would like the initial audit to cover: - the overall architecture and data pipeline; - possible data leakage, look-ahead bias, timestamp problems or unrealistic backtesting assumptions; - the current Elo features, probability model and calibration; - the use of bookmaker prices, market probabilities and closing line value; - whether the current methodology can realistically demonstrate independent edge; - tennis-specific data or features that should be added; - how to design a rigorous prospective validation process; - the most important technical and quantitative improvements, ordered by priority. Expected deliverables: 1. A written audit describing the main findings and risks. 2. A prioritized list of recommended changes. 3. A proposed validation and development roadmap. 4. A short call to discuss the findings and answer questions. I am particularly interested in your experience with sportsbook systems, odds aggregation, positive-EV analytics, historical odds and backtesting. I would also like to understand which of your previous projects involved predictive sports modelling or fair-probability estimation, rather than only scraping and bet execution. This initial engagement is intentionally small and paid. Please estimate how many hours you would need for a useful first audit. If the audit goes well, I would be open to continuing with a larger development phase. The source code would be shared only after an Upwork contract is established and would not include betting-account credentials or private API keys.
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