Fielding | R Documentation |
Fielding table
data(Fielding)
A data frame with 151507 observations on the following 18 variables.
playerID
Player ID code
yearID
Year
stint
player's stint (order of appearances within a season)
teamID
Team; a factor
lgID
League; a factor with levels AA
AL
FL
NL
PL
UA
POS
Position
G
Games
GS
Games Started
InnOuts
Time played in the field expressed as outs
PO
Putouts
A
Assists
E
Errors
DP
Double Plays
PB
Passed Balls (by catchers)
WP
Wild Pitches (by catchers)
SB
Opponent Stolen Bases (by catchers)
CS
Opponents Caught Stealing (by catchers)
ZR
Zone Rating
Lahman, S. (2024) Lahman's Baseball Database, 1871-2023, 2024 version, http://www.seanlahman.com/
data(Fielding)
# Basic fielding data
require("dplyr")
# Roberto Clemente's fielding profile
# pitching and catching related data removed
# subset(Fielding, playerID == "clemero01")[, 1:13]
Fielding %>%
filter(playerID == "clemero01") %>%
select(1:13)
# Yadier Molina's fielding profile
# PB, WP, SP and CS apply to catchers
Fielding %>%
subset(playerID == "molinya01") %>%
select(-WP, -ZR)
# Pedro Martinez's fielding profile
Fielding %>% subset(playerID == "martipe02")
# Table of games played by Pete Rose at different positions
with(subset(Fielding, playerID == "rosepe01"), xtabs(G ~ POS))
# Career total G/PO/A/E/DP for Luis Aparicio
Fielding %>%
filter(playerID == "aparilu01") %>%
select(G, PO, A, E, DP) %>%
summarise_each(funs(sum))
# Top ten 2B/SS in turning DPs
Fielding %>%
subset(POS %in% c("2B", "SS")) %>%
group_by(playerID) %>%
summarise(TDP = sum(DP, na.rm = TRUE)) %>%
arrange(desc(TDP)) %>%
head(., 10)
# League average fielding statistics, 1961-present
Fielding %>%
filter(yearID >= 1961 & POS != "DH") %>%
select(yearID, lgID, POS, InnOuts, PO, A, E) %>%
group_by(yearID, lgID) %>%
summarise_at(vars(InnOuts, PO, A, E), funs(sum), na.rm = TRUE) %>%
mutate(fpct = round( (PO + A)/(PO + A + E), 3),
OPE = round(InnOuts/E, 3))
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