ATP Match Prediction using Historical Data |Python ML

We are seeking a skilled data analyst or machine learning engineer to help us build a predictive model for ATP tennis matches based on historical data. The goal of the project is to develop a system that can accurately predict the outcome of ATP matches using a range of data sources, including player statistics, match results, and other relevant information. The ideal candidate should have experience in data analysis, machine learning, and data visualization, with a strong understanding of the ATP match ecosystem. They should be able to build and train a predictive model that can analyze large data sets and make accurate predictions based on historical data. The system should include the following features: A database of historical ATP match data, including player statistics and match outcomes A predictive model that can use this data to predict the outcome of future matches A user-friendly interface that allows users to input the current match conditions and receive a prediction of the match outcome Integration with real-time match data to allow for up-to-date predictions The candidate should be able to provide examples of similar projects they have worked on in the past, OR should have a strong understanding of machine learning techniques and algorithms. They should also be able to demonstrate their ability to work with large data sets and to visualize and present data in a meaningful way. We are looking for a candidate who can work independently and deliver the project on time and within budget. If you are interested in this project, please submit your proposal , your experience, and your estimated timeline and budget.