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Why Traditional Tennis Data Fails the Individual Player Tennis is deeply personal. Every player has unique strengths, patterns, and tendencies. Yet much of the data in tennis today is built on generalizations – averages, assumptions, and surface-level metrics that may look impressive but tell us little about your player or your game. At 135 Tennis … Read more
Tennis Data Systems and Processes that makes Sense There are many tennis data and analytics providers now operating in the market, all of them using a similarly based method of analytics that involves “traditional” methods of reporting. The problem is, data alone doesn’t drive improvement, especially when, as is often the case, a lot of … Read more
Why Players, Parents and Coaches Should Embrace Analytics Early In the world of junior tennis, the prevailing mindset often suggests that analytics and match analysis are tools reserved for older, more advanced players. Many young athletes don’t even consider engaging with analytics until they are nearing the end of their high school career, believing that … Read more
Why “Points Won on First Serve” is a Worthless Metric “Points won on 1st serve” is supposed to be a measure of 1st serve effectiveness. It’s not officially labeled that way, but that is precisely what it’s supposed to represent. The more points you win when your first serve goes in, the more effective your … Read more
Tennis is a Game of Errors? Not if you want to improve In tennis, if you add forced errors and unforced errors together, you can justify the statement “tennis is a game of errors”. The problem is it’s a really lazy way of reporting what happens in a tennis match. Consider these definitions: Unforced error … Read more
There’s a lot of talk about how much of tennis is short rallies. So, what importance do we put on practicing long rally patterns? Lots, and here are two reasons why.
If players want to improve, they have to know about their errors. Tennis has always made this process very confusing by only reporting unforced errors, rather than the difference between
In Part 1 of June workshops, we look at the way tennis analytics are displayed on TV and started to discuss how we need to measure improvement by recording the difference between a forced and an unforced error.
In Part 2 of our Workshops, we looked at how analytics tell the story of each point, “big data” and some of the stats that don’t matter.
In Part 3 of our June Workshops, we look at Player Profiling, Hard court v Clay court tennis, and the most common strategy mistakes made by developing players.