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.
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.
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.
Tennis is a big part of my personal life. Playing competitive level matches since 2006, I have won a few tournaments in the “club” level. Ironically, I have never played in a doubles tournament ( never a fan of doubles game, and often complain about not even getting sweaty), nor have I played in a game organized by the companies I worked for (tennis might be such a “minority” sport that didn’t get much attention).
I broke both rules last week.
It was the 1st “3M Open” tennis tournament – featured only doubles matches. One of my colleagues in the lab signed me up for it. We have played together a few times in the past but never played doubles as partners. For both of us, the original goal was very clear –
“Enjoy the sunshine and have some fun. “
In the end, we brought the “3M cup” back home by winning three straight matches in a row. When I look back today, the experience was 100% memorable. But “fun” is not the appropriate word. Instead, it is more of the mix of drama, pressure, heartbreak, teamwork, and a sense of relief.
As a self-claimed NTRP 4.0 tennis player, I am really proud of my passion for tennis. But I am writing this post not for sharing my passion and achievement of winning a tournament, but three pieces of learning I took away from it. Hopefully, they are helpful to my audience, no matter as a tennis fan or not.