Scrape tables of unequal lengths and fill with NA when html node is not present in R

I would like to scrape some tables off the wayback machine. The original website deletes their data after a period of time so I'm scraping off wayback for reproducibility. The pages have two types of tables of different lengths. I would like to scrape all of them and put them in the same data frame. The first type of table only has four columns while the second has 7. For simplicity, I'll only use two of the 400 links

I would like for the table to show NA for nodes that are not present on that page. So in the first photo, it would show NA for the columns adultWorldChamp, M1WorldChamp, and M2WorldChamp. I have an idea of what to do, but it doesn't quite work right.

Any guidance?

library(rvest); library(tidyverse)
library(RSelenium); library(netstat)

links2 = c("https://web.archive.org/web/20220000000000*/https://www.bjjcompsystem.com/tournaments/1869/categories/2053146",
"https://web.archive.org/web/20220000000000*/https://www.bjjcompsystem.com/tournaments/1869/categories/2053225")

# Start server
remote_driver = rsDriver(browser = 'firefox',
                         verbose = F,
                         port = free_port())
rd = remote_driver$client
rd$open()
rd$navigate('https://web.archive.org/web/20220000000000*/https://www.bjjcompsystem.com/tournaments/1869/categories/2053147&')
rd$maxWindowSize()

## create empty vector  
all.ranks = data.frame()

# Start scraping! ----
for (i in 1:2){
  rd$navigate(links2[i])
  Sys.sleep(10)
  date = rd$findElement(using = 'css', '.captures-range-info a:last-of-type')
  date$clickElement()
  Sys.sleep(10)
  
  # Get pg source to read html data
  html = read_html(rd$getPageSource()[[1]])
  
# define function to get basic info
getBasicInfo <- function(basic){

  # create a df with basic info
  df <- data.frame(rank = parseMatch(basic,'.prioriry-number', TRUE),
                   name = parseMatch(basic,'.competitor-name', TRUE),
                   gym = parseMatch(basic,'th+ td', FALSE),
                   grand_slam_pts = parseMatch(basic,'td:nth-child(3)', FALSE),
                   overall_pts = parseMatch(basic,'.text-center+ td', FALSE)) 

  return(df)
}

basic_info <- map_df(html, getBasicInfo)

# grab worlds info
worlds <- html %>% 
  html_elements(css = "td:nth-child(4) , td:nth-child(5) , td:nth-child(3)") %>% 
  html_text2()

# add worlds info to basic info 
all_info <- basic_info %>%
  mutate('AdultWorldChamp' = worlds[1],
         'M1WorldChamp' = worlds[2],
         'M2WorldChamp' = worlds[3])

  
all.ranks = rbind(all.ranks, all_info)
}