FieldingPost {Lahman}

FieldingPost data

Description

Post season fielding data

Usage

data(FieldingPost)

Format

A data frame with 15540 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)

Source

Lahman, S. (2023) Lahman's Baseball Database, 1871-2022, 2022 version, https://www.seanlahman.com/baseball-archive/statistics/

Examples

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