Today’s fantasy landscape grows more and more complex. When evaluating rookie prospects we have so many different stats and metrics to look at. The hard part is figuring out which ones are important and which do not matter. That is where regression analysis can come in and play a large role. I will be using regression analysis to help build a predictive grading model that can be used to easily sift through many players to quickly identify guys to avoid and target. Our end goal when selecting rookies is who will be the best fantasy assets when they hit the NFL, and the best assets are the ones who score us the most fantasy points. To create my rookie model I used regression analysis and sorted through multiple different metrics to determine which correlated to NFL fantasy points per game (FP/G) the most and which correlated the least.
Rookie RB Prospect Model: Regression Analysis
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