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Baseball Analytics
Win a Fantasy Baseball Championship with Free Analytics Data
How to Easily Access Fantasy Baseball Data for Analytics Projects
Fantasy baseball is a data-driven competition where analytics can give you a winning edge. In this guide, we’ll show you how to retrieve fantasy baseball data using R packages like baseballr and ffbaseball, allowing you to create your own projections, analyze player performance, and even connect to private leagues to run simulations.
Step 1: Utilizing R Packages for Fantasy Baseball Data
Several R packages are available to help you access and analyze fantasy baseball data. Here are some of the most valuable ones:
- baseballr: Provides tools to access public MLB data from sources like Baseball Savant, Statcast, and MLB’s Stats API, making it a valuable tool for analyzing player performance in fantasy baseball.
Example: Installing baseballr
install.packages("remotes")
remotes::install_github("BillPetti/baseballr")
Example: Retrieving MLB Data for Fantasy Baseball
library(baseballr)
# Get Baseball Savant data for a specific player in 2023
player_data <- statcast_search(playerid = 605141, year = 2023)
head(player_data)
This retrieves detailed player data, such as pitch speed and exit velocity, useful for fantasy baseball analysis.
- ffbaseball: Similar to ffverse for fantasy football, ffbaseball allows you to connect to private fantasy baseball leagues from platforms like Yahoo Fantasy, ESPN, and CBS.
Example: Connecting to a Private Yahoo Fantasy Baseball League
library(ffbaseball)
# Connect to Yahoo Fantasy Baseball league
yahoo_connection <- yahoo_connect(
season = 2023,
league_key = "mlb.l.12345", # Replace with your Yahoo league key
token = "YOUR_OAUTH_TOKEN" # Replace with your OAuth token
)
# Retrieve league standings
standings <- yahoo_standings(conn = yahoo_connection)
head(standings)
This connects to your Yahoo Fantasy Baseball league and retrieves standings, player stats, and more.
- ffpros: Fetches expert rankings, projections, and ADP (Average Draft Position) data for fantasy baseball from FantasyPros.
Example: Installing ffpros
install.packages("ffpros")
Example: Fetching FantasyPros ADP Data
library(ffpros)
# Retrieve FantasyPros ADP data for 2023
adp_data <- ffpros_adp(sport = "mlb")
head(adp_data)
This retrieves ADP data from FantasyPros, which you can use to analyze draft trends and player popularity.
Step 2: How to Connect to Private ESPN Fantasy Baseball Leagues
To connect to an ESPN fantasy baseball league, you’ll need the SWID and ESPN_S2 tokens, similar to fantasy football.
Finding Your ESPN SWID and ESPN_S2 Tokens
- Log in to ESPN: Open your browser and log in to your ESPN Fantasy Baseball account.
- Inspect the Website: Right-click anywhere on the page and select Inspect or press
Ctrl+Shift+I
(Windows) orCmd+Option+I
(Mac). - Find the Cookies: Go to the Application tab and look for
SWID
andESPN_S2
under thehttps://www.espn.com
domain. - Copy the Values: Save these tokens for your R connection.
Example: Connecting to ESPN Fantasy Baseball with ffbaseball
library(ffbaseball)
# Connect to ESPN fantasy baseball league
espn_connection <- espn_connect(
season = 2023,
league_id = 123456, # Replace with your league ID
espn_s2 = "YOUR_ESPN_S2", # Replace with your ESPN_S2 token
swid = "YOUR_SWID" # Replace with your SWID token
)
# Get standings or player stats
standings <- espn_standings(conn = espn_connection)
print(standings)
Step 3: Running League Simulations for Fantasy Baseball
Simulating league outcomes helps you project player performance and potential wins. Using packages like ffsimulator, you can simulate thousands of league outcomes based on player stats and settings.
Example: Running League Simulations with ffsimulator
library(ffsimulator)
# Run 5000 simulations for the connected league
simulation_results <- ff_simulate(conn = espn_connection, n_seasons = 5000)
# Visualize the simulation results
plot(simulation_results)
This simulates your fantasy baseball league’s schedule and projects win probabilities based on historical data.
Step 4: Projecting Player Performance with ffanalytics
The ffanalytics package allows you to project player performance across multiple seasons. It aggregates expert projections from various sources and can help you project player stats for upcoming games or seasons.
Example: Projecting Player Stats with ffanalytics
library(ffanalytics)
# Project player stats for 2023
projections <- run_projections(sport = "mlb", season = 2023, sources = c("ESPN", "FantasyPros", "MLB"))
head(projections)
This example projects player stats for the 2023 MLB season, helping you plan your fantasy baseball strategy.
Step 5: Analyze Draft Data with ffpros
Analyzing draft trends is critical to dominating your fantasy baseball league. Using ffpros, you can retrieve ADP data and expert rankings to gain insights into draft strategy.
Example: Fetching ADP Data for Fantasy Baseball
library(ffpros)
# Fetch FantasyPros ADP for fantasy baseball
adp_data <- ffpros_adp(sport = "mlb")
head(adp_data)
This retrieves ADP data for MLB players, helping you prepare for your draft by understanding where players are typically selected.
Step 6: Explore Public Fantasy Baseball Data Sources
In addition to R packages, several public data sources offer valuable fantasy baseball data:
- FantasyPros: Provides expert rankings, projections, and ADP data for fantasy baseball platforms.
- ESPN: Offers player stats, projections, and league data for ESPN fantasy baseball leagues.
- Yahoo Fantasy: Offers detailed stats, league data, and projections.
- CBS Fantasy Baseball: Provides player data, projections, and rankings.
- MLB Statcast: Offers advanced player statistics such as pitch data, exit velocity, and more.
Step 7: Apply Your Data Skills to Fantasy Baseball Analytics Projects
Now that you know how to access and analyze fantasy baseball data, it’s time to apply your skills to real-world projects. Whether you’re analyzing player projections, simulating league schedules, or strategizing for your draft, tools like baseballr and ffbaseball will give you a competitive edge.
Explore our Baseball Analytics Courses to learn more about data analysis techniques, custom models, and statistical approaches that will help you dominate your fantasy league.
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