Shiny application to graph the average number of offensive events (H, HR, SO, etc) per game per team over the history of Major League Baseball.

server.R

library(shiny)
library(Lahman)
library(ggplot2)

# Define server logic required to plot various variables against year
shinyServer(function(input, output) {
  
  # Compute the forumla text in a reactive function since it is 
  # shared by the output$caption and output$mpgPlot functions
  formulaText <- reactive({
    paste("Variable:", input$variable,
          "Per Game Per Team:",
          input$range[1], "to", input$range[2])
  })
  
  # Return the formula text for printing as a caption
  output$caption <- renderText({
    formulaText()
  })
  
  # Generate a plot of the requested variable against mpg and only 
  # include outliers if requested
  output$mpgPlot <- renderPlot({
    Teams.recent <- subset(Teams, yearID >= input$range[1] &
                                  yearID <= input$range[2])
    Teams.recent$stat.game <- Teams.recent[, input$variable] / Teams.recent[, "G"]
     print(ggplot(Teams.recent, aes(yearID, stat.game)) + geom_point() +
             geom_smooth(size=2, color="red", method="loess", 
                         span=input$decimal) + 
             xlab("YEAR") + ylab("RATE PER GAME PER TEAM")   
           )
  }, width=600, height=500)
})

ui.R

library(shiny)

# Define UI for miles per gallon application
shinyUI(pageWithSidebar(
  
  # Application title
  headerPanel("Offensive Production in Baseball History"),
  
  # Sidebar with controls to select the variable to plot against mpg
  # and to specify whether outliers should be included
  sidebarPanel(
    selectInput("variable", "Variable:",
                list("Runs" = "R",
                     "Hits" = "H", 
                     "Home Runs" = "HR", 
                     "Doubles" = "X2B",
                     "Triples" = "X3B",         
                     "Walks" = "BB",
                     "Strikeouts" = "SO",
                     "Stolen Bases" = "SB",
                     "Errors" = "E")),
    sliderInput("range", "Range:",
                min = 1901, max = 2012, format="###",
                value = c(1901, 2012), step = 1),
    sliderInput("decimal", "Loess Smoothing Fraction:", 
                min = 0.05, max = 0.95, value = 0.2, step= 0.05)
  ),
  
  # Show the caption and plot of the requested variable against mpg
  mainPanel(
    h3(textOutput("caption")),
    
    plotOutput("mpgPlot")
  )
))