FieldingPost data
Post season fielding data
data(FieldingPost)
A data frame with 15063 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. (2022) Lahman's Baseball Database, 1871-2021, 2021 version, https://www.seanlahman.com/baseball-archive/statistics/
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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