R Веб-парсинг?

Вы слишком рано звоните в as.numeric(), так как в счете все еще есть тире ('-'). Вот почему вы получаете NA.

Вы можете сделать следующее: (Я создал новый фрейм данных, содержащий только оценки).

library(rvest)
mens_bb <- read_html("http://gomason.com/schedule.aspx?path=mbball", na = c("NA")) 

mens_scores <- mens_bb %>%
  html_nodes("div.sidearm-schedule-game-result span:nth-child(3)") %>%
  html_text()

library(tidyr)
mens_df1 <- data.frame(mens_scores)
mens_df1 <- mens_df %>% separate(mens_scores, c("Mason_score", "Opponent_score"), sep = "\\-")
mens_df1$Mason_score <- as.numeric(mens_df1$Mason_score)
mens_average <- mean(mens_df1$Mason_score)
#71.84848

Вы должны сделать разделение перед преобразованием в numeric. Например, следующее даст вам желаемый результат.

mens_df <- data.frame(mens_scores)
mens_df %>% separate(mens_scores, c("Mason’s score", "Opponent’s score"), sep = "-") %>%
  mutate_all(as.numeric) %>% summarise_all(mean)

#   Mason’s score Opponent’s score
# 1         71.85            75.67

library(rvest)
library(tidyverse)

# read webpage/ extract only container with relevant info 
bb_mason <- read_html("http://gomason.com/schedule.aspx?path=mbball")  %>% 
            xml_find_all(".//ul[@class = 'sidearm-schedule-games-container']")

# vector with xpath to extract required info
bb_xpath <- c(opponent = ".//span[@class = 'sidearm-schedule-game-opponent-name']/a",
       location = ".//div[@class = 'sidearm-schedule-game-location']/span[1]",
       result = ".//div[@class = 'sidearm-schedule-game-result text-italic']/span[2]",
       score = ".//div[@class = 'sidearm-schedule-game-result text-italic']/span[3]")

# sapply all xpath values, fetch information, and store in data frame tibble
bb_df <- tbl_df(
             sapply(bb_xpath, function(x) { 
                                    bb_mason %>% 
                                      xml_find_all(x) %>%
                                      xml_text(trim = T) }))

# separate scores, replace values in result column with more appropriate values,
# convert to numeric, and calculate average
bb_df %>% 
  separate("score", c("mason", "opp"), sep = "-") %>% 
  mutate(mason = as.numeric(mason), 
         opp = as.numeric(opp),
         result = plyr::mapvalues(result, c("W,", "L,"), c("Won", "Lost"))) %>% 
  group_by(result) %>% 
  summarize(avg.score = mean(mason))

Конечный результат:

#  A tibble: 2 x 2
#   result avg.score
#   <chr>      <dbl>
# 1 Lost        65.7
# 2 Won         78.4