July 30, 2021

Jonas Trostle

Figures

nflfastR

Defense

Cornerback performance is hard to measure, but we can try.

June 27, 2021

Richard Anderson

nflfastR

stan

We build a series of models to estimate team ability from EPA data

June 7, 2021

Ben Baldwin

Torch

Machine learning

Computer vision

Coverage classification Using CNNs.

April 17, 2021

Ben Baldwin

xgboost

nflfastR

xgboost and R

Feb. 5, 2021

Ben Baldwin

Figures

nflfastR

Decision Trees

xgboost

Model Calibration

A description of the nflfastR Expected Points (EP), Win Probability (WP), Completion Probability (CP) Expected Yards after Catch (xYAC), and Expected Pass (xPass) models.

Feb. 5, 2021

David Anderson

Quarterback Analysis

nflfastR

Stupid Internet Arguments

Quantifying Quarterbacks' performance along the "game manager" and "gunslinger" dimensions.

Feb. 4, 2021

Ben Dominguez

python

scikit-learn

Game Prediction

Use Python and scikit-learn to model NFL game outcomes and build a pre-game win probability model.

Jan. 21, 2021

Jack Lichtenstein

nflfastR

EPA

Penalty EPA

Prediction

Use nflfastR to calculate penalty EPA and understand the randomness of penalties to improve prediction accuracy of game outcomes

Jan. 11, 2021

Adrian Cadena

nflfastR

Articles

Home Field Advantage

Multi-season analysis of league and team-specific home-field advantage in the NFL.

Dec. 29, 2020

Jack Lichtenstein

nflfastR

EPA

Adjusting EPA

Rolling EPA

Prediction

Use nflfastR to develop lagged rolling averages of EPA to best predict a game's outcome

Oct. 3, 2020

Peter Owen

The more you look into the numbers, the better it looks for Aaron Rodgers

Sept. 26, 2020

Arthur Gymer

Figures

nflfastR

Positional breakdown

Receiving

Breaking down the receiving game by position using nflfastR data.

Sept. 9, 2020

Mike Irene

field goal

nflfastR

placekicker

Using nflfastR play-by-play data to measure kicker performance.

Sept. 8, 2020

Richard Anderson

tidyModels

nflfastR

stan

This article shows how to use tidyModels to predict QB dropbacks and uses a multilevel model to show which teams are run/pass heavy after accounting for game script

Sept. 6, 2020

Dennis Brookner

Raphael Laden-Guindon

Exonerating punters for long returns

Aug. 31, 2020

Ben Baldwin

nflfastR

Articles

Does incorporating actual rest time help us predict how a defense will do?

Aug. 31, 2020

Anthony Reinhard

Fantasy Football

nflfastR

nflfastR xYAC Model

Use the nflfastR xYAC & CP models to calculate how many fantasy points an average receiver would expect to earn on each target.

Aug. 29, 2020

Jonathan Goldberg

Scraping

Game Predicitions

nflfastR

Here, we'll look at how to scrape ESPN's and 538's pregame predictions and merge them into nflfastR data

Aug. 29, 2020

Analytics Darkweb

Figures

Animation

nflfastR

Combining lessons from multiple posts to create faceted or animated heatmaps.

Aug. 29, 2020

Ethan Douglas

nflfastR

python

Methods for modeling density estimates and expected completion percentages across the football field for individual players.

Aug. 28, 2020

Analytics Darkweb

Efficiency

Loading your nfl data at 10x speed!

Aug. 27, 2020

Adrian Cadena

Logistic Generalized Additive Mixed Models

Mixed Effects

Completion Probability Intercept

Case study how to leverage Generalized Additive Mixed Models (GAMM) to estimate the individual probability of completion per Quarterback as a random effect.

Aug. 26, 2020

Sam Hoppen

Figures

nflfastR

Fantasy Football

Using nflfastR data to visualize where on the field running backs get their carries and how that translates to the Trivial Rush Attempt Percentage (TRAP) model.

Aug. 25, 2020

Anthony Gadaleta

Figures

nflfastR

turnovers

quarterbacks

Building expected interceptions and expected fumbles models to find QBs likely to increase or decrease their interceptions and/or turnovers per dropback from 2019 to 2020.

Aug. 24, 2020

Ben Baldwin

Getting started

Collection of short answers to common questions.

Aug. 24, 2020

Sebastian Carl

Scraping

espnscrapeR

Interactive plots

Total QBR

Figures

How to get ESPN data and create interactive plots using the plotly ggplot2 library.

Aug. 23, 2020

Austin Ryan

Tidymodels

Figures

nflfastR

Looking at what metrics are important for predicting wins. Creating expected season win totals and comparing to reality.

Aug. 22, 2020

Robby Greer

Elo

python

Use 538's QB Elo value, a highly predictive measurement of QB impact, to compare QB careers across era

Aug. 21, 2020

Max Bolger

nflfastR

python

Game excitement calculation and a win probability figure.

Aug. 21, 2020

Ethan Douglas

nflfastR

python

Methods for visualizing NFL passing location data.

Aug. 21, 2020

Austin Ryan

Figures

nflfastR

CPOE / EPA functions

Packers

A look into Rodgers Efficiency Decline. Also some functions for plotting EPA/CPOE moving averages.

Aug. 20, 2020

Anthony Reinhard

Figures

nflfastR

Using nflfastR data to show how much more efficient passing is than rushing at the team level

Aug. 20, 2020

Jonathan Goldberg

Opponent adjusted EPA

Figures

nflfastR

This article shows how to adjust a team's EPA per play for the strength of their opponent. The benefits of adjusted EPA will be demonstrated as well!

Aug. 20, 2020

Ben Baldwin

nflfastR

python

Showing how to contribute using Python code

Aug. 19, 2020

Analytics Darkweb

Figures

Roster

nflfastR

Rebuilding player graphs when ID keys go missing or are corrupted.

Aug. 19, 2020

Analytics Darkweb

Keras

Tensorflow

nflfastR

Using Keras in R to build neural networks.

Aug. 19, 2020

Ben Baldwin

Figures

nflfastR

Do quarterbacks who get hit see their performance decline throughout the game?

Aug. 19, 2020

Sebastian Carl

Figures

nflfastR

This article looks at the percentage of snaps with win probability over an arbitralily chosen critical value and compares it with the true win percentage.

Aug. 18, 2020

Sebastian Carl

Scraping

PFR

Figures

nflfastR

This article shows how to scrape football data from Pro Football Reference and how to plot the bad throw percentage data for quarterbacks.

- Articles (39)
- Adjusting EPA (1)
- Animation (1)
- Articles (2)
- Completion Probability Intercept (1)
- Computer vision (1)
- CPOE / EPA functions (1)
- Decision Trees (1)
- Defense (1)
- Efficiency (1)
- Elo (1)
- EPA (2)
- espnscrapeR (1)
- Fantasy Football (2)
- field goal (1)
- Figures (15)
- Game Predicitions (1)
- Game Prediction (1)
- Getting started (1)
- Home Field Advantage (1)
- Interactive plots (1)
- Keras (1)
- Logistic Generalized Additive Mixed Models (1)
- Machine learning (1)
- Mixed Effects (1)
- Model Calibration (1)
- nflfastR (30)
- nflfastR xYAC Model (1)
- Opponent adjusted EPA (1)
- Packers (1)
- Penalty EPA (1)
- PFR (1)
- placekicker (1)
- Positional breakdown (1)
- Prediction (2)
- python (6)
- Quarterback Analysis (1)
- quarterbacks (1)
- Receiving (1)
- Rolling EPA (1)
- Roster (1)
- scikit-learn (1)
- Scraping (3)
- stan (2)
- Stupid Internet Arguments (1)
- Tensorflow (1)
- tidyModels (1)
- Tidymodels (1)
- Torch (1)
- Total QBR (1)
- turnovers (1)
- xgboost (2)

If you see mistakes or want to suggest changes, please create an issue on the source repository.

Text and figures are licensed under Creative Commons Attribution CC BY-NC 4.0. Source code is available at https://github.com/mrcaseb/open-source-football, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

©2020 - Website creator Sebastian Carl (Twitter: @mrcaseb)