Salaries {Lahman} | R Documentation

## Salaries table

### Description

Player salary data.

### Usage

    data(Salaries)

### Format

A data frame with 26428 observations on the following 5 variables.

`yearID`

  Year

`teamID`

  Team; a factor

`lgID`

  League; a factor

`playerID`

  Player ID code

`salary`

  Salary

### Details

There is no real coverage of player's salaries until 1985.

### Source

Lahman, S. (2017) Lahman's Baseball Database, 1871-2016, 2016 version, http://www.seanlahman.com/baseball-archive/statistics/

### Examples

    # what years are included?
    summary(Salaries$yearID)

    # how many players included each year?
    table(Salaries$yearID)

    # Team salary data

    require("dplyr")
    require("ggplot2")

    # Total team salaries by league, team and year
    teamSalaries <- Salaries %>%
                      group_by(lgID, teamID, yearID) %>%
                      summarise(Salary = sum(as.numeric(salary))) %>%
                      group_by(yearID, lgID) %>%
                      arrange(desc(Salary))

    #######################################
    # Highest paid players each year:
    maxSal <- Salaries %>%
                group_by(yearID) %>%
                filter(salary == max(salary))
    maxPlayers <- bind_rows(lapply(maxSal$playerID, playerInfo)) %>%
                      select(-playerID)
    maxSal <- bind_cols(maxPlayers, maxSal)

    # Plot maximum MLB salary by year (1985-present)
    ggplot(maxSal, aes(x = yearID, y = salary/1e6)) +
       geom_point() +
       geom_smooth(se = FALSE) +
       labs(x = "Year", y = "Salary (millions)")

    # Plot salary distributions by year for all players
    ggplot(Salaries, aes(x = factor(yearID), y = salary/1e5)) +
       geom_boxplot(fill = "lightblue", outlier.size = 1) +
       labs(x = "Year", y = "Salary ($100,000)") +
       coord_flip()

    # Plot median MLB salary per year
    Salaries %>%
       group_by(yearID) %>%
       summarise(medsal = median(salary)) %>%
       ggplot(., aes(x = yearID, y = medsal/1e6)) +
       geom_point() +
       geom_smooth() +
       labs(x = "Year", y = "Median MLB salary (millions)")

    # add salary to Batting data
    batting <- Batting %>%
                  filter(yearID >= 1985) %>%
                  left_join(select(Salaries, playerID, yearID, teamID, salary),
                             by=c("playerID", "yearID", "teamID"))
    str(batting)

    #######################################
    # Average salaries by teams, over years
    #######################################

    # Some franchises are multiply named, so add a new variable
    # 'franchise' to the Salaries data as a lookup table

    franchise <- c(`ANA` = "LAA", `ARI` = "ARI", `ATL` = "ATL",
                   `BAL` = "BAL", `BOS` = "BOS", `CAL` = "LAA",
                   `CHA` = "CHA", `CHN` = "CHN", `CIN` = "CIN",
                   `CLE` = "CLE", `COL` = "COL", `DET` = "DET",
                   `FLO` = "MIA", `HOU` = "HOU", `KCA` = "KCA",
                   `LAA` = "LAA", `LAN` = "LAN", `MIA` = "MIA",
                   `MIL` = "MIL", `MIN` = "MIN", `ML4` = "MIL",
                   `MON` = "WAS", `NYA` = "NYA", `NYM` = "NYN",
                   `NYN` = "NYN", `OAK` = "OAK", `PHI` = "PHI",
                   `PIT` = "PIT", `SDN` = "SDN", `SEA` = "SEA",
                   `SFG` = "SFN", `SFN` = "SFN", `SLN` = "SLN",
                   `TBA` = "TBA", `TEX` = "TEX", `TOR` = "TOR",
                   `WAS` = "WAS")

    Salaries$franchise <- unname(franchise[Salaries$teamID])

    # Average salaries annual salaries by team, in millions USD
    avg_team_salaries <- Salaries %>%
        group_by(yearID, franchise, lgID) %>%
        summarise(salary= mean(salary)/1e6) %>%
        filter(!(franchise == "CLE" & lgID == "NL"))

    # Spaghetti plot of team salary over time by team
    # Yankees have largest average team salary since 2003
    ggplot(avg_team_salaries,
           aes(x = yearID, y = salary, group = factor(franchise))) +
           geom_path() +
           labs(x = "Year", y = "Average team salary (millions USD)")

[Package Lahman version 6.0-0 Index]