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Exploratory Analysis in Power BI
With all the data together, the next step in our Fantasy Basketball Optimization series is to do some basic exploratory analysis on the data. We’ll use a tool called Power BI for…
4 min read
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Automate Python with AWS Lambda
AWS Lambda is a serverless compute service provided by Amazon Web Services that allows you to easily and efficiently automate Python code in the cloud. When we needed to automate our Data…
4 min read
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Addressing the Lock-in Dilemma
So far in our Fantasy Basketball Optimization series, we put together a relational database of CSV files with stats and other league info and did some basic exploratory analysis in Power BI.…
4 min read
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Fantasy Basketball Optimization
We used data science and analytics to optimize our fantasy basketball team, eventually leading to a league championship! This series outlines how, including the full stats theory behind it and an automated…
4 min read
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Managing the Lock-in Spreadsheet
This post focuses on the third and final source in our Fantasy Basketball Optimization database: the lock-in spreadsheet. While the Sleeper API provided a lot of good league info, it didn’t tell…
4 min read
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Pulling Data from the Sleeper API
This next post in our Fantasy Basketball Optimization series focuses on our second data source: the Sleeper API. The Sleeper fantasy app provides a variety of different API endpoints for users to…
4 min read