MLB 2024 Season Stats

Author

Ben

Introduction

I am going to be performing an analysis on data from the 2024 MLB season. Each row is a player who had more than 100 plate appearances throughout the season. This data covers stats like batting average, hits, home runs, etc. You can learn more at this link: MLB data. You can download my data here: My data

Research Question

Which age group of players has the most power on average?

Method

I want to see a visual that groups players by age and compares the average number of home runs by those grouped ages. I will need to group ages together using mutate to create those groups and also find the mean home run amounts of that group. I will be using player_age and home_runs to create a visual.

Analysis

Players between the ages of 30-34 hit significantly more home runs than any other age which means power most likely comes from a mix of experience and athleticism. This is important to know because as a player gets older, you might be less inclined to sign them to a contract because they may not have the same power that they used to, and you should not expect as many home runs from a younger player who lacks experience.

--- title: "MLB 2024 Season Stats" author: "Ben" editor: visual toc: true # Generates an automatic table of contents. format: # Options related to formatting. html: # Options related to HTML output. code-tools: TRUE # Allow the code tools option showing in the output. embed-resources: TRUE # Embeds all components into a single HTML file. execute: # Options related to the execution of code chunks. warning: FALSE # FALSE: Code chunk sarnings are hidden by default. message: FALSE # FALSE: Code chunk messages are hidden by default. echo: FALSE --- ## Introduction I am going to be performing an analysis on data from the 2024 MLB season. Each row is a player who had more than 100 plate appearances throughout the season. This data covers stats like batting average, hits, home runs, etc. You can learn more at this link: [MLB data](https://baseballsavant.mlb.com/leaderboard/custom?year=2024&type=batter&filter=&min=100&selections=player_age%2Cab%2Cpa%2Chit%2Csingle%2Cdouble%2Ctriple%2Chome_run%2Cstrikeout%2Cwalk%2Cbatting_avg%2Cslg_percent%2Con_base_percent%2Con_base_plus_slg%2Cb_rbi%2Cb_lob%2Cb_total_bases%2Cr_total_caught_stealing%2Cr_total_stolen_base%2Cb_hit_by_pitch%2Cr_run%2Csprint_speed&chart=false&x=player_age&y=player_age&r=no&chartType=beeswarm&sort=1&sortDir=asc). You can download my data here: [My data](https://myxavier-my.sharepoint.com/:x:/g/personal/mccabeb1_xavier_edu/ETX_cJ0oWAhGrRXpBcZTr_4Bwh-ie_Me7J5iMXHZpBjMBw?download=1) ```{r} #| label: setup #| include: false library(tidyverse) # For all the tidy things, yo library(skimr) # For better summary statistics ``` ```{r} #| label: load data #| message: FALSE mlb <- read_csv("https://myxavier-my.sharepoint.com/:x:/g/personal/mccabeb1_xavier_edu/ETX_cJ0oWAhGrRXpBcZTr_4Bwh-ie_Me7J5iMXHZpBjMBw?download=1") ``` ## Research Question Which age group of players has the most power on average? ## Method I want to see a visual that groups players by age and compares the average number of home runs by those grouped ages. I will need to group ages together using mutate to create those groups and also find the mean home run amounts of that group. I will be using player_age and home_runs to create a visual. ```{r} #| label: analysis mlb %>% mutate(age_group = cut(player_age, breaks = c(20, 24, 29, 34, 39), labels = c("20-24", "25-29", "30-34", "35-39"), right = TRUE)) %>% filter(!is.na(age_group)) %>% group_by(age_group) %>% summarize(age_hr = mean(home_run, na.rm = TRUE)) %>% ggplot(aes(x = age_group, y = age_hr,)) + geom_col() + scale_y_continuous(labels = scales::comma) + labs(title = "Average Home Runs per Age Group", x = "Age Group", y = "Average Home Runs") ``` ## Analysis Players between the ages of 30-34 hit significantly more home runs than any other age which means power most likely comes from a mix of experience and athleticism. This is important to know because as a player gets older, you might be less inclined to sign them to a contract because they may not have the same power that they used to, and you should not expect as many home runs from a younger player who lacks experience.