One of the team members is a powerlifter who wanted to explore a topic related to powerlifting. Brainstorming a topic related to powerlifting brought us to the question of how sex, event, and bodyweight affect powerlifting attempts.
We performed a lot of data wrangling, exploratory analysis, and ran regressions on the data to answer our research question: Does weight class, event (type of lift: squat, bench press, or deadlift), and gender affect the percentage(%) increase in attempt weight selection(amount of weight the competitor chooses for their next attempt)? For example, given that an athlete has lifted 100kg in an event defined previously, would something like gender or weight class influence whether they pick 105 kg, 110 kg, or more for their next attempt?
We built our project entirely on Jupyter Notebook and utilized GitHub for version control.
The main challenges we faced were handling the data correctly and extensively to ensure we do not get abnormal values or anomalies in our analysis, and when running the regressions.
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