Okay, so I wanted to get into some sports data analysis, and I figured the best way to start was by looking at a recent NBA game. I chose the Phoenix Suns vs. Minnesota Timberwolves match because, well, it was a game that caught my eye. I’m not gonna lie, I’m a bit of a Timberwolves fan, so that played a part in it. Plus, this game had some serious playoff implications, which made it even more interesting.
First off, I needed to find the player stats for this game. That was step one. You can’t do much analysis without the actual data, right? I mean, that’s kind of obvious.
I started by searching around a bit. I hit up a few of the usual sports websites. You know, the big names. It took a little digging, but I finally found what I was looking for. A nice, clean table of all the player stats from the game. Points, rebounds, assists, steals, blocks, the whole nine yards. It was all there. I copied this data and then pasted it into a spreadsheet. Nothing fancy, just a simple spreadsheet to keep things organized.
Once I had all the data in one place, I started playing around with it. I wanted to see who really stood out in the game. You know, who were the top performers? Who had a rough night?
- I sorted the data by points to see who scored the most.
- Then I looked at rebounds to see who was dominating the boards.
- Assists were next. Gotta see who was dishing out the most dimes.
After going through all the stats, I started to get a better picture of how the game played out. Like, who was really making things happen for each team. For example, I noticed that one player had a crazy number of points, but not many rebounds or assists. So, he was clearly the go-to scorer, but maybe not the most well-rounded player.
Observations
It was cool to see how the stats backed up what I saw when I watched the game. It’s one thing to watch a game and have a feel for who played well, but it’s another thing to actually see the numbers. It gives you a whole new level of understanding. From the data, I figured out who the key players were for each team, and how they contributed to the overall game.
This was just a quick little project, but it was definitely a fun one. I feel like I learned a lot about how to analyze basketball stats, and it gave me some ideas for other things I want to explore. This is probably just the beginning of my sports data analysis journey.
