FieldingPost | R Documentation |
Post season fielding data
data(FieldingPost)
A data frame with 16606 observations on the following 17 variables.
playerID
Player ID code
yearID
Year
teamID
Team; a factor
lgID
League; a factor with levels AL
NL
round
Level of playoffs
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
TP
Triple Plays
PB
Passed Balls
SB
Stolen Bases allowed (by catcher)
CS
Caught Stealing (by catcher)
Lahman, S. (2024) Lahman's Baseball Database, 1871-2023, 2024 version, http://www.seanlahman.com/
require("dplyr")
## World Series fielding record for Yogi Berra
FieldingPost %>%
filter(playerID == "berrayo01" & round == "WS")
## Yogi's career efficiency in throwing out base stealers
## in his WS appearances and CS as a percentage of his
## overall assists
FieldingPost %>%
filter(playerID == "berrayo01" & round == "WS" & POS == "C") %>%
summarise(cs_pct = round(100 * sum(CS)/sum(SB + CS), 2),
cs_assists = round(100 * sum(CS)/sum(A), 2))
## Innings per error for several selected shortstops in the WS
FieldingPost %>%
filter(playerID %in% c("belanma01", "jeterde01", "campabe01",
"conceda01", "bowala01"), round == "WS") %>%
group_by(playerID) %>%
summarise(G = sum(G),
InnOuts = sum(InnOuts),
Eper9 = round(27 * sum(E)/sum(InnOuts), 3))
## Top 10 center fielders in innings played in the WS
FieldingPost %>%
filter(POS == "CF" & round == "WS") %>%
group_by(playerID) %>%
summarise(inn_total = sum(InnOuts)) %>%
arrange(desc(inn_total)) %>%
head(., 10)
## Most total chances by position
FieldingPost %>%
filter(round == "WS" & !(POS %in% c("DH", "OF", "P"))) %>%
group_by(POS, playerID) %>%
summarise(TC = sum(PO + A + E)) %>%
arrange(desc(TC)) %>%
do(head(., 1)) # provides top player by position
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