Note by Bill, Sweep Sports Analytics:
This is a great interesting analysis that Angel Maldonado asked to be published. I like the approach he takes here and the simplicity with which he addresses a few complex ideas. For all you Python enthusiasts, Angel has shared the code and you can replicate it on your machine. If you have any questions, you can reach him at angelnmaldonado94@gmail.com.
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Introduction
I created this in hopes of actively practicing my Python and visualization skills towards a topic that I am passionate about.
I am a die hard Lakers fan and feel that this year has been a rollercoaster that never ends (keep in mind that I hate rollercoasters, yet here I am) I love the Lakers but hate that there were so many gambles and situations that did not pan out the way they were supposed to. . . . .
No one could have predicted this considering the Lakers had won the championship just about 2 years ago.
The 2020-2021 season showed us that our beloved team clearly had Championship Hangover. The year was plagued by a short turn around after winning the 2020 season, following several nagging injuries to key players, Lebron James and Anthony Davis. As a result, the team ended the year 42-30 which led to a First round playoff exit at the hands of the Phoenix Suns.
The 2021-2022 NBA season was supposed to be a very promising one for the Los Angeles Lakers, the front office made several acquisitions and trades to bring some veteran leadership and injecting some youth into the team.
On paper, this was believed to be one of the favorited teams to win the Championship.
Against the huge spotlight that was centered around the Lakers, they currently are sitting in the 9th spot of the Western Conference of the NBA with a disappointing 26-30 record.
Before looking into the data, let’s frame together the narrative of how this team came together.