Real-Time 1xBet Crash Predictor

JavaScript, Python, Software Architecture, C++ Programming, Data Science, NumPy, Data Analysis, Pandas · I need a working predictor for the 1xBet Crash game that can analyse incoming information on the fly and issue an estimated crash point before each round starts. The engine must run real-time calculations but train itself exclusively on historical sports data that I will provide (CSV format). No other feeds are necessary at this stage.

The core of the job is to design, code and test a lightweight model that can ingest the historical dataset, learn patterns quickly, and then keep refining its coefficients while the game is live. Python with Pandas, NumPy, scikit-learn or a comparable ML stack is fine, as long as the final script can execute on a standard VPS and output the next “safe cash-out” multiplier through a simple CLI or REST endpoint.

Please include: • Clean, well-commented source code • Brief README with setup instructions and model explanation • A short demonstration (video or screen-share) showing the predictor running in real time against a few live rounds

I will consider the task complete once the predictor connects, announces its forecast before each round, and logs accuracy stats for at least 100 consecutive games.