boxball VS baseballr

I haven't worked with BI tools, but I'll make the same recommendation for Retrosheet data that I always do: check out the Boxball distributions, specifically the CSV files (or the parquet files if you prefer). You can load those right in, rather than futzing with Retrosheet's event files and processing them manually, etc., just to get to the same spot.

The original data source is the Baseball Databank (aka "The Lahman Database"). I use the Boxball distributions, which include both retrosheet and Baseball Databank data.

You know, I thought about that after posting, that the dailies might not be available directly from retrosheet. I use the Boxball distributions, which take the retrosheet data and process it into database images. These distributions include a "daily" table with the daily logs. So apparently Boxball is generating that table.

I used to think the same thing, and then I found the Boxball pre-built images. You still have to be a bit handy to get them working, but it's way easier than starting from scratch with raw retrosheet data. I initially used the postgres image and worked in SQL, and then switched to python/pandas and the parquet files.

I've always been good with data, math, Excel, etc., but decided to take it to another level during the pandemic. The most difficult thing about Retrosheet data is getting into a usable format. Luckily, the boxball project has created a number of ready-to-download images with all of the data, for different database technologies.

For Retrosheet data, I've been using pre-built images from Boxball, rather than going through the whole process of downloading and converting the files from retrosheet. The Boxball images are awesome. I mostly use the Parquet files for Pandas, but they have other formats (e.g., postgres Docker images, CSV, etc) there.

A basic understanding of R should be enough if you install the baseball r package. From there you can scrape off of Baseball Reference or Fangraphs for custom date ranges to get stats on whatever time frame basis you would like. Then you can export/copy/whatever to excel if you want, or do the analysis right in R.

Source: MLB Stats API via baseballr.

I like this idea, too! I use baseballr all the time. It is a godsend.

In order to make it, I need to get every lineup from every game in the season. I am using the baseballr package to get the game_pk number. Each game has a game_pk number, and each lineup is tied to that game_pk. So I need to create a dataframe (all_games_list) for each game with its game_pk number in it, and then use the game_pk numbers to create a new dataframe (lineup_all) that contains the lineup for said game_pk.

I just remembered there is also this R package: Acquiring and Analyzing Baseball Data • baseballr.

To get all the data, I would suggest checking out baseballr if you are familiar with R. https://billpetti.github.io/baseballr/

Visualization originally posted on my blog - I built the boxplot using R and ggplot2, and was fortunate to be able to use the excellent baseballr package to query MLB game information for the runtime source data!

baseballR (baseball)

most folks without direct access to mlb's api scrape baseball savant's data api. packages like baseballr or pybaseball can help with this. remember, this is in the open on a trust model: no commercial use, and don't hammer the api.

If you're using R, this is the gold standard package to use for getting baseball data. This helps you scrape data.