(latest version released 2018-05-29)
baseballr is a package written for R focused on baseball analysis. It
includes functions for scraping various data from websites, such as
FanGraphs.com, Baseball-Reference.com, and baseballsavant.com. It also
includes functions for calculating metrics, such as wOBA, FIP, and
team-level consistency over custom time frames.
You can read more about some of the functions and how to use them at its official site as well as this Hardball Times article.
You can install baseballr from github with:
# install.packages("devtools")
devtools::install_github("BillPetti/baseballr")The package consists of two main sets of functions: data acquisition and metric calculation.
For example, if you want to see the standings for a specific MLB
division on a given date, you can use the standings_on_date_bref()
function. Just pass the year, month, day, and division you want:
library(baseballr)
standings_on_date_bref("2015-08-01", "NL East", from = FALSE)
#> $`NL East_up to_2015-08-01`
#> Tm W L W-L% GB RS RA pythW-L%
#> 1 WSN 54 48 0.529 -- 422 391 0.535
#> 2 NYM 54 50 0.519 1.0 368 373 0.494
#> 3 ATL 46 58 0.442 9.0 379 449 0.423
#> 4 MIA 42 62 0.404 13.0 370 408 0.455
#> 5 PHI 41 64 0.390 14.5 386 511 0.374Right now the function works as far as back as 1994, which is when both leagues split into three divisions.
You can also pull data for all hitters over a specific date range. Here are the results for all hitters from August 1st through October 3rd during the 2015 season:
library(dplyr)
data <- daily_batter_bref("2015-08-01", "2015-10-03") %>%
head()In terms of metric calculation, the package allows the user to calculate
the consistency of team scoring and run prevention for any year using
team_consistency():
team_consistency(2015)
#> # A tibble: 30 x 5
#> Team Con_R Con_RA Con_R_Ptile Con_RA_Ptile
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 ARI 0.37 0.39 43 80
#> 2 ATL 0.38 0.36 65 25
#> 3 BAL 0.4 0.36 88 25
#> 4 BOS 0.37 0.39 43 80
#> 5 CHC 0.41 0.37 97 50
#> 6 CHW 0.38 0.36 65 25
#> 7 CIN 0.36 0.38 22 63
#> 8 CLE 0.38 0.42 65 100
#> 9 COL 0.38 0.38 65 63
#> 10 DET 0.39 0.35 82 3
#> # … with 20 more rowsYou can also calculate wOBA per plate appearance and wOBA on contact for any set of data over any date range, provided you have the data available.
Simply pass the proper data frame to woba_plus:
data %>%
filter(PA > 200) %>%
woba_plus %>%
arrange(desc(wOBA)) %>%
select(Name, Team, season, PA, wOBA, wOBA_CON) %>%
head()
#> Name Team season PA wOBA wOBA_CON
#> 1 Shin-Soo Choo Texas 2015 260 0.430 0.495
#> 2 Francisco Lindor Cleveland 2015 259 0.404 0.468
#> 3 Jose Altuve Houston 2015 262 0.372 0.406
#> 4 Adam Eaton Chicago 2015 262 0.367 0.436
#> 5 Manny Machado Baltimore 2015 266 0.362 0.396
#> 6 Matt Duffy San Francisco 2015 264 0.312 0.338You can also generate these wOBA-based stats, as well as FIP, for
pitchers using the fip_plus() function:
daily_pitcher_bref("2015-04-05", "2015-04-30") %>%
fip_plus() %>%
select(season, Name, IP, ERA, SO, uBB, HBP, HR, FIP, wOBA_against, wOBA_CON_against) %>%
arrange(desc(IP)) %>%
head(10)
#> season Name IP ERA SO uBB HBP HR FIP wOBA_against
#> 1 2015 Johnny Cueto 37.0 1.95 38 4 2 3 2.62 0.210
#> 2 2015 Dallas Keuchel 37.0 0.73 22 11 0 0 2.84 0.169
#> 3 2015 Sonny Gray 36.1 1.98 25 6 1 1 2.69 0.218
#> 4 2015 Mike Leake 35.2 3.03 25 7 0 5 4.16 0.240
#> 5 2015 Felix Hernandez 34.2 1.82 36 6 3 1 2.20 0.225
#> 6 2015 Corey Kluber 34.0 4.24 36 5 2 2 2.40 0.295
#> 7 2015 Jake Odorizzi 33.2 2.41 26 8 1 0 2.38 0.213
#> 8 2015 Josh Collmenter 32.2 2.76 16 3 0 1 2.82 0.290
#> 9 2015 Bartolo Colon 32.2 3.31 25 1 0 4 3.29 0.280
#> 10 2015 Zack Greinke 32.2 1.93 27 7 1 2 3.01 0.240
#> wOBA_CON_against
#> 1 0.276
#> 2 0.151
#> 3 0.239
#> 4 0.281
#> 5 0.272
#> 6 0.391
#> 7 0.228
#> 8 0.330
#> 9 0.357
#> 10 0.274The edge_scrape() function allows the user to scrape PITCHf/x data
from the GameDay application using Carson Sievert’s
pitchRx package and to calculate
metrics associated with
Edge%. The function
returns a dataframe grouped by either pitchers or batters and the
percentge of pitches in each of the various Edge zones.
Example (pitchers):
edge_scrape("2015-04-06", "2015-04-07", "pitcher") %>%
select(-6:-4, -13) %>%
head(10)
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_tormlb_nyamlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_minmlb_detmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_colmlb_milmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_bosmlb_phimlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_balmlb_tbamlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_nynmlb_wasmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_atlmlb_miamlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_chamlb_kcamlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_anamlb_seamlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_pitmlb_cinmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_sdnmlb_lanmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_clemlb_houmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_texmlb_oakmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_sfnmlb_arimlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_07/gid_2015_04_07_atlmlb_miamlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_07/gid_2015_04_07_balmlb_tbamlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_07/gid_2015_04_07_colmlb_milmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_07/gid_2015_04_07_sfnmlb_arimlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_07/gid_2015_04_07_texmlb_oakmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_07/gid_2015_04_07_anamlb_seamlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_07/gid_2015_04_07_sdnmlb_lanmlb_1/inning/inning_all.xml
#> # A tibble: 10 x 9
#> pitcher_name pitcher All_pitches Upper_Edge Lower_Edge Inside_Edge
#> <chr> <dbl> <int> <dbl> <dbl> <dbl>
#> 1 Bartolo Col… 112526 86 0.035 0.07 0.058
#> 2 LaTroy Hawk… 115629 12 0.083 0.333 0
#> 3 Joe Nathan 150274 4 0 0 0
#> 4 Buddy Carly… 234194 9 0 0.222 0
#> 5 Jason Grilli 276351 14 0 0 0.214
#> 6 Kevin Gregg 276514 17 0 0.059 0.118
#> 7 Joaquin Ben… 276542 19 0 0 0.158
#> 8 Ryan Vogels… 285064 99 0.01 0.071 0.141
#> 9 Jeremy Affe… 346793 5 0 0 0.4
#> 10 Grant Balfo… 346797 21 0.095 0 0
#> # … with 3 more variables: Outside_Edge <dbl>, Heart <dbl>,
#> # Out_of_Zone <dbl>Example (batters):
edge_scrape("2015-04-06", "2015-04-07", "batter") %>%
select(-6:-4, -13) %>%
head(10)
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_tormlb_nyamlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_minmlb_detmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_colmlb_milmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_bosmlb_phimlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_balmlb_tbamlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_nynmlb_wasmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_atlmlb_miamlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_chamlb_kcamlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_anamlb_seamlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_pitmlb_cinmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_sdnmlb_lanmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_clemlb_houmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_texmlb_oakmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_06/gid_2015_04_06_sfnmlb_arimlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_07/gid_2015_04_07_atlmlb_miamlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_07/gid_2015_04_07_balmlb_tbamlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_07/gid_2015_04_07_colmlb_milmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_07/gid_2015_04_07_sfnmlb_arimlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_07/gid_2015_04_07_texmlb_oakmlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_07/gid_2015_04_07_anamlb_seamlb_1/inning/inning_all.xml
#> http://gd2.mlb.com/components/game/mlb/year_2015/month_04/day_07/gid_2015_04_07_sdnmlb_lanmlb_1/inning/inning_all.xml
#> # A tibble: 10 x 9
#> batter_name batter All_pitches Upper_Edge Lower_Edge Inside_Edge
#> <chr> <dbl> <int> <dbl> <dbl> <dbl>
#> 1 Bartolo Co… 112526 7 0 0 0.429
#> 2 Torii Hunt… 116338 19 0 0.158 0.105
#> 3 David Ortiz 120074 18 0 0 0.111
#> 4 Alex Rodri… 121347 17 0 0 0.353
#> 5 Aramis Ram… 133380 23 0 0.087 0.217
#> 6 Adrian Bel… 134181 26 0 0.038 0.154
#> 7 Carlos Bel… 136860 22 0.091 0 0.136
#> 8 Michael Cu… 150212 14 0 0.143 0.143
#> 9 Jimmy Roll… 276519 41 0.024 0.146 0.049
#> 10 Ryan Vogel… 285064 10 0 0.1 0.3
#> # … with 3 more variables: Outside_Edge <dbl>, Heart <dbl>,
#> # Out_of_Zone <dbl>More functionality will be added soon. Please leave any suggestions or bugs in the Issues section.