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Fangraphs

MLB Prediction Showdown: Fangraphs vs. FiveThirtyEight

8 minute read

Published:

In 2008, Nate Silver created the website FiveThirtyEight with the goal of using data-driven analysis to raise the bar of political coverage and predictions (Link). Silver also has history with baseball analytics, creating a player performance forecast model called PECOTA and writing for Baseball Prospectus. So it was no surprise when FiveThirtyEight rolled out a model to predict MLB games in 2016.

FiveThirtyEight

MLB Prediction Showdown: Fangraphs vs. FiveThirtyEight

8 minute read

Published:

In 2008, Nate Silver created the website FiveThirtyEight with the goal of using data-driven analysis to raise the bar of political coverage and predictions (Link). Silver also has history with baseball analytics, creating a player performance forecast model called PECOTA and writing for Baseball Prospectus. So it was no surprise when FiveThirtyEight rolled out a model to predict MLB games in 2016.

MLB

MLB Prediction Showdown: Fangraphs vs. FiveThirtyEight

8 minute read

Published:

In 2008, Nate Silver created the website FiveThirtyEight with the goal of using data-driven analysis to raise the bar of political coverage and predictions (Link). Silver also has history with baseball analytics, creating a player performance forecast model called PECOTA and writing for Baseball Prospectus. So it was no surprise when FiveThirtyEight rolled out a model to predict MLB games in 2016.

NFL

Peterman’s Ineptitude: Web Scraping with Pandas Read_HTML

4 minute read

Published:

On December 19th, the Oakland Raiders shocked the football community by signing Nathan Peterman to their practice squad after a terrible year with the Buffalo Bills. Advanced stats aren’t really needed to describe how poorly Peterman played. A 54.3% completion percentage, a 30.7 quarterback rating, and a 1/7 TD/INT ratio did just fine demonstrating how bad he was.

Nathan Peterman

Peterman’s Ineptitude: Web Scraping with Pandas Read_HTML

4 minute read

Published:

On December 19th, the Oakland Raiders shocked the football community by signing Nathan Peterman to their practice squad after a terrible year with the Buffalo Bills. Advanced stats aren’t really needed to describe how poorly Peterman played. A 54.3% completion percentage, a 30.7 quarterback rating, and a 1/7 TD/INT ratio did just fine demonstrating how bad he was.

QBR

Peterman’s Ineptitude: Web Scraping with Pandas Read_HTML

4 minute read

Published:

On December 19th, the Oakland Raiders shocked the football community by signing Nathan Peterman to their practice squad after a terrible year with the Buffalo Bills. Advanced stats aren’t really needed to describe how poorly Peterman played. A 54.3% completion percentage, a 30.7 quarterback rating, and a 1/7 TD/INT ratio did just fine demonstrating how bad he was.

This Week in Sports Analytics

pandas

MLB Prediction Showdown: Fangraphs vs. FiveThirtyEight

8 minute read

Published:

In 2008, Nate Silver created the website FiveThirtyEight with the goal of using data-driven analysis to raise the bar of political coverage and predictions (Link). Silver also has history with baseball analytics, creating a player performance forecast model called PECOTA and writing for Baseball Prospectus. So it was no surprise when FiveThirtyEight rolled out a model to predict MLB games in 2016.

Peterman’s Ineptitude: Web Scraping with Pandas Read_HTML

4 minute read

Published:

On December 19th, the Oakland Raiders shocked the football community by signing Nathan Peterman to their practice squad after a terrible year with the Buffalo Bills. Advanced stats aren’t really needed to describe how poorly Peterman played. A 54.3% completion percentage, a 30.7 quarterback rating, and a 1/7 TD/INT ratio did just fine demonstrating how bad he was.