The aim of Squash Stats is to advance squash through data. This will be done with the aid of data science which uses scientific methods and processes, algorithms and systems to extract knowledge and insight from data. It employs techniques and theories drawn from many fields within the context of mathematics, statistics, computer science and information science. By implementing these methods we hope to push the boundaries of what analytical tools are available to analyze in squash. This includes following advances in AI and applying cutting-edge computer vision techniques and machine learning algorithms to publicly available squash data.
For more details on our mission statement please see our article The Story of Squash Stats and to see our current team please see our About Us section. You can view our already published blog posts here: Blog Posts.
While we endeavor to achieve these goals it will entail a lot of time, work and expertise from different areas such as research, mathematics, machine learning, data science, programming, visualizations, multimedia, sports journalism, and above all, a love for the sport of squash. In the Squash Stats project we are very aware of the demands of the modern life style, both in terms of a professional and personal/family aspect. The project is thus run at a pace which is determined by the individuals with no hard deadlines. Each individual essentially works on the project in their spare time. Given the ethos of the project, it currently does not receive or provide a monetary reward.
We are thus looking to expand our area of expertise and man-power to help accelerate Squash Stats in providing unique statistics and articles on squash. If you have skills and experience that you think may help us on our quest and would like to join our project please contact us on our Facebook page Squash Stats. The following are some of the skills we are looking for but not exclusively:
Graphic Design – Multimedia: Creation of multimedia visualizations, promotional graphs, info-graphs, video snippets to help promote our articles and results.
Sports writer: We are looking for somebody to help write, review and add to our blog articles which will be based on our data analysis. In this case a good knowledge of squash and the history of squash would be beneficial but not entirely necessary.
Video Analysis & Image Recognition: We wish to create a performance analysis tool (in python) which will analyze video footage of squash matches to determine parameters such as ball speed, travel patterns, rally lengths, winning shot positions, number of shots, player positioning etc etc.
Data Science: We have ample data on tournaments, matches, scorelines, player profiles etc and many ideas of what we would like to explore and analyze. But all this takes time. We therefore require people that are willing to take the data, analyze it, create visualization and to write articles.
We are looking forward to hearing from you.
Squash Stats Team