nba_carmelo: The Complete History Of The NBA 2017-18 NBA Predictions

Description

The raw data behind the story "The Complete History Of The NBA" https://projects.fivethirtyeight.com/complete-history-of-the-nba/ and our "2017-18 NBA Predictions" https://projects.fivethirtyeight.com/2018-nba-predictions/

Usage

nba_carmelo

Arguments

Format

Because of R package size restrictions, only a preview of the first 10 rows of this dataset is included; to obtain the entire dataset (1871 to 2017 games) see Examples below. A data frame with 10 rows representing games and 20 variables:

date: Date
season: Season year, 1947-2018
neutral: TRUE if the game was played on neutral territory, FALSE if not
playoff: TRUE if the game was a playoff game, FALSE if not
team1: The name of one participating team
team2: The name of the other participating team
elo1_pre: Team 1's Elo rating before the game
elo2_pre: Team 2's Elo rating before the game
elo_prob1: Team 1's probability of winning based on Elo rating
elo_prob2: Team 2's probability of winning based on Elo rating
elo1_post: Team 1's Elo rating after the game
elo2_post: Team 2's Elo rating after the game
carmelo1_pre: Team 1's CARMELO rating before the game
carmelo2_pre: Team 2's CARMELO rating before the game
carmelo1_post: Team 1's CARMELO rating after the game
carmelo2_post: Team 2's CARMELO rating after the game
carmelo_prob1: Team 1's probability winning based on CARMELO rating
carmelo_prob2: Team 2's probability of winning based on CARMELO rating
score1: Points scored by Team 1
score2: Points scored by Team 2

Examples

Run this code

# NOT RUN {
# To obtain the entire dataset, run the following code:
library(tidyverse)
library(janitor)
nba_carmelo <- read_csv("https://projects.fivethirtyeight.com/nba-model/nba_elo.csv") %>%
  clean_names() %>%
  mutate(
    team1 = as.factor(team1),
    team2 = as.factor(team2),
    playoff = ifelse(playoff == "t", TRUE, FALSE),
    playoff = ifelse(is.na(playoff), FALSE, TRUE),
    neutral = ifelse(neutral == 1, TRUE, FALSE)
  )
# }

Run the code above in your browser using DataCamp Workspace