Season Recap

The Nationals won the World Series and it was awesome. They beat the Astros? I can’t remember. Anyway the Astros were stealing signs, so it’s good the Nats won.

The Washington Nationals
Used to be the Montreal Expos.
Allez les ’pos!

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My Experience of the Season

What Games I Went To During the Season

  • April 30 vs. Cubs Nats won 7-3
  • May 21 vs. Cardinals Nats lost 4-6
  • June 30 vs. Mets: double header
    • Game 1: Won 5-2
    • Game 2: Lost 3-0
  1. April 30 vs. Cubs Nats won 7-3
  2. May 21 vs. Cardinals Nats lost 4-6
  3. June 30 vs. Mets: double header
    1. Game 1: Won 5-2
    2. Game 2: Lost 3-0
Day High temp Low temp
Monday 105 86
Tuesday 102 82
Wednesday 100 80
Thursday 108 81

Two Photos That Illustrate the Season

World Series

Game Date Score Location Time Attendance
1 October 22 Washington Nationals – 5, Houston Astros – 4 Minute Maid Park 3:43 43,339
2 October 23 Washington Nationals – 12, Houston Astros – 3 Minute Maid Park 4:01 43,357
3 October 25 Houston Astros – 4, Washington Nationals – 1 Nationals Park 4:03 43,867
4 October 26 Houston Astros – 8, Washington Nationals – 1 Nationals Park 3:48 43,889
5 October 27 Houston Astros – 7, Washington Nationals – 1 Nationals Park 3:19 43,910
6 October 29 Washington Nationals – 7, Houston Astros – 2 Minute Maid Park 3:37 43,384
7 October 30 Washington Nationals – 6, Houston Astros – 2 Minute Maid Park 3:42 43,326

Nationals Players

First I will load the libraries I need:

library(tidyverse)
library(knitr)
library(DT)

Roster

nats <- read_csv("nationals.csv")
natspitch <- read_csv("nationalspitching.csv")

Next I will keep only the position, name, and age of each player with the select() function:

nats2 <- select(nats, Pos, Name, Age)
datatable(nats2)

This document was compiled on 2020-07-31 17:33:30.

There are 50 players on the Nationals.

Team Statistics

Hitting

nats3 <- select(nats, Pos, Name, AB, RBI, HR, BA)
datatable(nats3)

Pitching

nats4 <- select(natspitch, Pos, Name, W, L, ERA)
datatable(nats4)

Batting average vs. home runs

ggplot(nats, aes(x=BA, y=HR)) + geom_point()
## Warning: Removed 14 rows containing missing values (geom_point).