| FieldingPost | R Documentation | 
Post season fielding data
data(FieldingPost)A data frame with 16606 observations on the following 17 variables.
playerIDPlayer ID code
yearIDYear
teamIDTeam; a factor
lgIDLeague; a factor with levels AL NL
roundLevel of playoffs
POSPosition
GGames
GSGames Started
InnOutsTime played in the field expressed as outs
POPutouts
AAssists
EErrors
DPDouble Plays
TPTriple Plays
PBPassed Balls
SBStolen Bases allowed (by catcher)
CSCaught 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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