mlb_players_18 {openintro}

Batter Statistics for 2018 Major League Baseball (MLB) Season

Description

Batter statistics for 2018 Major League Baseball season.

Usage

mlb_players_18

Format

A data frame with 1270 observations on the following 19 variables.

name

Player name

team

Team abbreviation

position

Position abbreviation: 1B = first base, 2B = second base, 3B = third base, C = catcher, CF = center field (outfield), DH = designated hitter, LF = left field (outfield), P = pitcher, RF = right field (outfield), SS = shortstop.

games

Number of games played.

AB

At bats.

R

Runs.

H

Hits.

doubles

Doubles.

triples

Triples.

HR

Home runs.

RBI

Runs batted in.

walks

Walks.

strike_outs

Strike outs.

stolen_bases

Stolen bases.

caught_stealing_base

Number of times caught stealing a base.

AVG

Batting average.

OBP

On-base percentage.

SLG

Slugging percentage.

OPS

On-base percentage plus slugging percentage.

Source

https://www.mlb.com/stats

See Also

mlbbat10, mlb

Examples

d <- subset(mlb_players_18, !position %in% c("P", "DH") & AB >= 100)
dim(d)

# _____ Per Position, No Further Grouping _____ #
plot(d$OBP ~ as.factor(d$position))
model <- lm(OBP ~ as.factor(position), d)
summary(model)
anova(model)

# _____ Simplified Analysis, Fewer Positions _____ #
pos <- list(
  c("LF", "CF", "RF"),
  c("1B", "2B", "3B", "SS"),
  "C"
)
POS <- c("OF", "IF", "C")
table(d$position)

# _____ On-Base Percentage Across Positions _____ #
out <- c()
gp <- c()
for (i in 1:length(pos)) {
  these <- which(d$position %in% pos[[i]])
  out <- c(out, d$OBP[these])
  gp <- c(gp, rep(POS[i], length(these)))
}
plot(out ~ as.factor(gp))
summary(lm(out ~ as.factor(gp)))
anova(lm(out ~ as.factor(gp)))