nflpredictr

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Model Details

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The nflpredictr R package provides a lightweight R client for retrieving predictions for upcoming (and past) NFL games via the NFL Win Predictor API. Details on the model used to make the predictions can be found here

nflpredictr provides four main functionalities:

1. Retrieves new data to use as the inputs into a ML model trained to predict the outcomes of NFL games
2. Provide the new data to the API and return predictions
3. Visualize results.
4. Retrieve Las Vegas Odds and lines to compare with the predictions generated from nflpredictr

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Installation

You can install the development version of nflpredictr from GitHub with:

# install.packages("devtools")
devtools::install_github("anguswg-ucsb/nflpredictr")

Example

nflpredictr provides utility functions for accessing game predictions from a Logistic Regression ML model that was trained on ~20 years of historic NFL data and correctly predicts the outcomes of games ~69% of the time. If no inputs are given to predict_games(), the default behavior is to make a prediction for week 2 of the 2021 NFL season.

# Load package
library(nflpredictr)

# Make an API request using predict_games(), default week is the upcoming week of the season
nflpredictr::predict_games(
  year = 2021,
  week = 2
)
#> 
#> 
#> Sending request to nflwinpredictor API...
#> Request URL:
#> http://68.183.25.9:8000/predict-new-data?year=2021&pred_week=2
#> # A tibble: 16 × 8
#>    season  week game_id         home_team away_team win   home_win_prob away_w…¹
#>     <int> <int> <chr>           <chr>     <chr>     <chr>         <dbl>    <dbl>
#>  1   2021     2 2021_02_SF_PHI  PHI       SF        1             0.699    0.301
#>  2   2021     2 2021_02_TEN_SEA SEA       TEN       1             0.694    0.306
#>  3   2021     2 2021_02_MIN_ARI ARI       MIN       1             0.692    0.308
#>  4   2021     2 2021_02_ATL_TB  TB        ATL       1             0.644    0.356
#>  5   2021     2 2021_02_LV_PIT  PIT       LV        1             0.618    0.382
#>  6   2021     2 2021_02_DAL_LAC LAC       DAL       1             0.572    0.428
#>  7   2021     2 2021_02_BUF_MIA MIA       BUF       1             0.544    0.456
#>  8   2021     2 2021_02_KC_BAL  BAL       KC        1             0.540    0.460
#>  9   2021     2 2021_02_HOU_CLE CLE       HOU       1             0.509    0.491
#> 10   2021     2 2021_02_NYG_WAS WAS       NYG       0             0.498    0.502
#> 11   2021     2 2021_02_NO_CAR  CAR       NO        0             0.471    0.529
#> 12   2021     2 2021_02_NE_NYJ  NYJ       NE        0             0.449    0.551
#> 13   2021     2 2021_02_CIN_CHI CHI       CIN       0             0.443    0.557
#> 14   2021     2 2021_02_DEN_JAX JAX       DEN       0             0.417    0.583
#> 15   2021     2 2021_02_LA_IND  IND       LA        0             0.413    0.587
#> 16   2021     2 2021_02_DET_GB  GB        DET       0             0.312    0.688
#> # … with abbreviated variable name ¹​away_win_prob

Make predictions on past games

Predictions can also be requested for weeks of past NFL seasons, going as far back as the 2016 season.

# Make an API request using predict_games() for a specific year and week
nflpredictr::predict_games(
  year = 2018,
  week = 8
  )
#> 
#> 
#> Sending request to nflwinpredictor API...
#> Request URL:
#> http://68.183.25.9:8000/predict-new-data?year=2018&pred_week=8
#> # A tibble: 14 × 8
#>    season  week game_id         home_team away_team win   home_win_prob away_w…¹
#>     <int> <int> <chr>           <chr>     <chr>     <chr>         <dbl>    <dbl>
#>  1   2018     8 2018_08_GB_LA   LA        GB        1             0.758    0.242
#>  2   2018     8 2018_08_CLE_PIT PIT       CLE       1             0.729    0.271
#>  3   2018     8 2018_08_NYJ_CHI CHI       NYJ       1             0.683    0.317
#>  4   2018     8 2018_08_DEN_KC  KC        DEN       1             0.650    0.350
#>  5   2018     8 2018_08_MIA_HOU HOU       MIA       1             0.639    0.361
#>  6   2018     8 2018_08_SF_ARI  ARI       SF        1             0.563    0.437
#>  7   2018     8 2018_08_TB_CIN  CIN       TB        1             0.561    0.439
#>  8   2018     8 2018_08_BAL_CAR CAR       BAL       1             0.555    0.445
#>  9   2018     8 2018_08_SEA_DET DET       SEA       1             0.552    0.448
#> 10   2018     8 2018_08_NO_MIN  MIN       NO        1             0.524    0.476
#> 11   2018     8 2018_08_PHI_JAX JAX       PHI       0             0.440    0.560
#> 12   2018     8 2018_08_WAS_NYG NYG       WAS       0             0.406    0.594
#> 13   2018     8 2018_08_IND_LV  LV        IND       0             0.397    0.603
#> 14   2018     8 2018_08_NE_BUF  BUF       NE        0             0.317    0.683
#> # … with abbreviated variable name ¹​away_win_prob

Make a tile plot of win probabilities

nflpredictr contains a few functions for quick plotting the outputs from predict_games(). The plot_tile() function will plot each match up side by side on a tile plot and color code teams by their predicted win probability from the NFL Win Prediction API.

# Plot the outputs from predict_games()
tile_plot <- nflpredictr::plot_tile(
                  predictions = nflpredictr::predict_games(
                    year = 2021,
                    week = 5
                  )
              )

Plot the teams favored to win that week

The plot_favored() function will plot the teams favored by the NFL Win Prediction API model in order of win probability.

# Plot the outputs from predict_games()
fav_plot <- nflpredictr::plot_favored(
                predictions = nflpredictr::predict_games(
                                  year = 2021,
                                  week = 5
                                ),
                prob_alpha  = FALSE
                )