Big data and analytics are having a major impact in sports - they have become essential for elite sports coaching, prediction and the enhancement of broadcasting. This has been possible because sophisticated technologies for collecting spatio-temporal data in sports have been developed. There is a real interest for sports analytics at the amateur level but unfortunately the availability of such technologies is still limited to the top tournaments due to their cost and requirements. In previous work we presented a lowcost technology for collecting tennis spatio-temporal data in real-time while being highly portable and non-intrusive. In this paper, we show that our system can also lead to valuable analysis of the game. Players and ball movements have been analysed separately and a combination of both has led to the extraction of higher level information. In contrast to previous work, we present an-end-to-end low-cost system for tennis analytics that goes from data collection to data analysis visualization.
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