This summer, I decided to try something new for my tennis journey by actively participating in UTR (Universal Tennis Registry) . This was also inspired by UTR’s increased popularity in Shanghai , where I was visiting last year. I am seeing it thru my own eyes that it was no longer just a rating used in North America (mostly in US).
In this post, I’d like share my experience this summer with UTR. In total I paid $80 for two leagues tournament. I will be covering
How to UTR rating system works (vs NTRP and WTN)
Its “power users’ price & value from a non-US resident perspective
Overall experience for me after completing first 6 ranked matches
UTR (Universal Tennis Rating) is a globally recognized rating system for tennis players. After being an outsider looking for a few years, I finally played my first UTR tournament (Flex League) in Toronto. Overall the experience was positive, despite losing a close match in 3 sets. In this post, I’d like to share my overall experience and my match breakdown.
Finally, I am able to play my first outdoor game, recorded using my newest equipment fence cap (bought on Black Friday 2021). It is a pro-set game with Kevin – my doubles partner from Credit Valley Club Inter-county “B” team. We didn’t play very often recently, as he spent more time on doubles and I focused on singles match plays.
The game was played at Glen Abby community part upon my request. The weather is cloudy with mild wind conditions, 8 degrees celsius in early after. I believe this to be an ideal weather condition for tennis, but Kevin feels it is a bit too cold. He said the balls feel too hard with the cold temperate. My topspin heavy style neutralized the bad weather condition, as I usually don’t need to hit the ball perfectly to generate points.
For the actual scores, I won the 1st set 8:3 by winning the last 4 games straight. The 2nd set was much closer and ended with 1-1 when the times ran out (the total score for the 2nd set was 15-15).
My conditioning is still nowhere close to my peak level. If we have enough time to finish, the 2nd set would be a lot closer. Fatigue seems to impact me much more than Kevin.
What I like about my game today is I was able to hit 2 winners on the forehand cross-court, each with over 85km/h on the line. I don’t usually attack that angle on my previous matches
What is interesting is my backhand slice shots type % – only 28% slices. I used to only use slices on my backhand so this is definitely encouraging to see. It could also indicate Kevin didn’t attack my backhand with deep balls much.
This holiday I got another tech toy – an M1 powered MacBook Pro 13”. One of the reasons to justify my buying decision is I will be able to “produce” more tennis tracking videos using the Mac version of the SwingVision. In this post, I’d like to share my initial review of it, after using it for a couple of sessions.
In a normal situation, I would wait for a few more weeks to get a bit more hands-on experience. Unfortunately, the city I live in imposed a new lock-down measure, essentially blocking any indoor tennis over the winter. The plan is to keep updating this with more information available.
Key takeaways & recommendations
SwingVision on Mac is a working version that can analyze video captured from any recording device with a minimum of 720p and 30fps.
The convenience of viewing and editing the video on a bigger screen with a Mac provides a better user experience.
The post-game editing feature is still limited since SwingVision doesn’t allow for exporting video in the Mac for now. However, it doesn’t limit any video edit by tools like iMovie to pre-process the imported video
If you are an apple watch user to tag the game with real-time scoring, I don’t suggest you wait a bit. The current combination will result in losing the real-time scoring capabilities since the video and the watch stats isn’t talking to each other.
I received a special gift from my lovely wife during last year’s Christmas.
It is an add-on lens to put on my iPhone to capture more area. It is particularly useful when recording the tennis match from the baseline, because my iPhone doesn’t have a wide angle lens built-in so it doesn’t capture enough area.
To be honest, originally I was just planning to try out the new AI feature offered by SwingVision app. After using it for over 6 weeks and multiple rounds of trial and errors, post game video has become an essential piece of my tennis life. The app itself is still in its infancy stage with all kinds of limitations, however I can see a lot of potential in this area.
Back by popular demand, this blog post continues diving into making use of the data we captured via Swing App from my Apple Watch.
If you are new to the tennis tracking via apple watch, please check out my introductory blog post.
If you are interested in tennis, and subscribed to the Pro version of the Swing App, you will be able to export all the data to a clean Excel format. That is really cool, but what can you do about it?
In this blog, I will share my experience of playing and analyzing the raw data for over 30 hrs over the past few months. Hopefully by reading this article, you will have slightly more incentive to make use of the data, after your hard fought game and logging via Apple Watch.
We will cover the following three topics with hands-on examples:
Basic data cleaning and data modeling for the required analysis using Excel build-in feature
How to breakdown the first and second serve performance with speed and distribution
How to breakdown the short, medium and long rally on game points
During the winter of 2018-2019, I was able to take my tennis tracking journey into a new level. By now most of my tennis hitting partners are calling me a “data nerd”, clicking my watch like crazy during the game. But when I show them the stats after the game, they all (seem to be) impressed.
I did the following two new things in particular:
Used the “Point by Point + ” score tracking in the Swing App to track all the points I have played. In total, I tracked 18 matches over the last 4 month, all of them were single matches and played in 1 hour.
Exported the captured data into spreadsheets. By analyzing the data set, I was able to identify some of the limitations, as well as some opportunities to further enhance the analytics experience.
Before we dive in, if you are interested in knowing the tennis tracking tools and methodology, or a high-level overview, you can check my 1st blog post of this series: Tennis tracking after 18 month of usage. Or if you prefer to track drills instead of match, you can check out my last post on advanced tennis shots tracking.
It has been 9 months since I first shared experience to track tennis performance with Apple Watch. Backing up by popular demand(Surprised so many visitors found this blog from search engine all over the world), I’d like to take it further with a more in-depth review, of my own experience tracking and analyzing my tennis workout with the Swing app.
Playing tennis has been a major part of my adult life: It is fun, competitive and a truly global sport. More importantly, it has shaped my character and my social network. Over the past 18 months, I have been using my Apple Watch to track, and subsequently, to analyze my tennis performance along with swimming
In this post, we will cover the background, the pros and cons of different apps, and how the additional metrics playing a role in my mindset shift.
