{"id":2743,"date":"2022-12-20T05:27:53","date_gmt":"2022-12-20T05:27:53","guid":{"rendered":"http:\/\/optimumsportsperformance.com\/blog\/?p=2743"},"modified":"2022-12-20T15:04:51","modified_gmt":"2022-12-20T15:04:51","slug":"box-dotplots-for-performance-visuals","status":"publish","type":"post","link":"https:\/\/optimumsportsperformance.com\/blog\/box-dotplots-for-performance-visuals\/","title":{"rendered":"Box & Dotplots for Performance Visuals"},"content":{"rendered":"

A colleague recently asked me about visualizing athlete performance of athletes relative to their teammates. More specifically, they wanted something that showed some sort of team average and normal range and then a way to highlight where the individual athlete of interest resided within the population.<\/p>\n

Immediately, my mind went to some type of boxplot visualization combined with a dotplot where the athlete can clearly identified. Here are a few examples I quickly came up with.<\/p>\n

Simulate Performance Data<\/strong><\/span><\/p>\n

First we will simulate some performance data for a group of athletes.<\/p>\n

\r\n### Load libraries -----------------------------------------------\r\nlibrary(tidyverse)\r\nlibrary(randomNames)\r\n\r\n### Data -------------------------------------------------------\r\nset.seed(2022)\r\ndat <- tibble(\r\n  participant = randomNames(n = 20),\r\n  performance = rnorm(n = 20, mean = 100, sd = 10))\r\n<\/pre>\n
Plot 1 – Boxplot with Points
\n<\/strong><\/span><\/p>\n
The first plot is a simple boxplot plot with dots below it.<\/p>\n
A couple of notes:<\/p>\n