Around this time last year, I wrote a post dissecting the decline of The Simpsons from its peak in the mid 90s finding that the golden age of the show spanned an incredible 214 episodes. As a comparison, Friends, which seemed to have been on TV forever, managed 236 episodes in total. Given this longevity, I was happy to accept that such a decline was inevitable, if not long overdue. However, many explanations were offered for the fall: the start, and success, of Family Guy forcing the show to branch away from its roots into zanier territory; some watershed episodes such as The Principal and the Pauper, or 22 Short Films about Springfield fundamentally changing the formula of the show; or the glut of celebrity cameos shoehorned into the show—compare Lady Gaga’s cameo with, say, Dustin Hoffman’s appearance as Mr Bergstrom. However, one explanation that came up frequently was that the downfall coincided with a shift in the writers of the show.

To examine this, I grabbed a list of all The Simpsons episodes, their writers, and their respective IMDb ratings. I’m not going to pretend that IMDb is an oracle when it comes to ratings—Big Bang Theory has a rating of 8.2/10 for starters—later Simpsons episodes have much fewer ratings than earlier episodes, and it’s likely those ratings are skewed in some way. If I really hated seasons 15-20, I’m unlikely to watch, and therefore rate, seasons 20+. So, IMDb ratings are far from perfect, but they’re the best I have available to me without resorting to my own subjective ratings.

Much to my surprise, The Simpsons has had over a hundred writers throughout its life. While a few are regular contributors, many have only written once or twice. For this analysis I only considered those writers credited with ten or more episodes. Although most episodes have a single writer credited, many have more than one. While I’m not familiar with the writing process of The Simpsons, I’m sure that even where a single writer is credited, the writing was the product of more than one person. For example, Conan O’ Brien is often noted as playing an important role in The Simpsons throughout the early 90s, yet he only has 4 writing credits. I gathered the average rating across all episodes by writers contributing more than ten episodes. Where an episode had shared writing credits, I treated it as though each writer wrote an individual episode with the rating of that episode.

Topping the list of writers is the pair of Bill Oakley and Josh Weinstein, who co-wrote all their episodes and were showrunners throughout seasons seven and eight. Between them they wrote classic episodes such as Lisa vs Malibu Stacey, Bart vs Australia, and, although I mentioned 22 Short Films about Springfield as being seen as something of a harbinger of the decline, Bill Oakley is credited with the enormously popular steamed hams scene.

Although the presentation of the results above might suggest some failing on the part of writers towards the bottom of the list, bear in mind these writers all wrote 10+ episodes of The Simpsons.

But, how does this translate into a decline in the quality of the show over time? One way to look at this might be to get an estimate of what rating we might expect an episode to have considering just the average rating of the writers credited on that episode.

This does show what we would expect, if every writer wrote a perfectly average episode every time they were credited, the show would have begun declining some time around its 200th episode. The steady line of points you see here just above 7.5 is the ‘Other’ category, the average rating of episodes involving writers with fewer than ten writing credit. Interestingly, the white line, showing a smoothed average rating of episodes, falls below the average rating of ‘Other’ writers for the first time at episode 213, just one episode earlier than my previous post found the golden age to have ended.

However, this still doesn’t quite get at the question: did a change in writing staff prompt a change in the quality in the show? It’s possible writers who contributed to great early episodes have lower averages simply because they stayed with the show long enough. Something about living long enough to see yourself become the villain. To check this, I looked at which episodes writers were involved in:

The writers are sorted as before, according to the average rating of the episodes the respective writers were involved in. It’s clear to see that as we move down the writers (thus moving into lower average ratings), there is a trend towards writers whose contributions began later in the show’s run. While this still may not mean a change in writers caused the drop in quality—200+ episodes is a long time to maintain quality—but it certainly lends some weight to the claim.

All the results in this post were done in R, with plots done in ggplot2 and subsequently touched up in Inkscape. If you’re interested in how I got the data together then read on, otherwise you might be interested in my other Simpsons-related posts: When did the golden age of The Simpsons end?), What is the best/most quotable Simpsons episode?, and Who is the main side character in The Simpsons?

The writers data were sourced from Wikipedia, while the ratings were sourced from IMDb using the R package rvest. For the most part this was an exercise in using regular expressions to get the text data cleaned up.

library(rvest)
library(tidyverse)

simpsons_writers_1 <- simpsons_wiki_1 %>%
html_nodes(".wikiepisodetable") %>%
html_table()

simpsons_writers_2 <- simpsons_wiki_2 %>%
html_nodes(".wikiepisodetable") %>%
html_table(fill = TRUE)

# Remove the movie and other non-standard episode tables
simpsons_writers_1[[19]] <- NULL
simpsons_writers_2[c(4, 12)] <- NULL

simpsons_writers <- rbind(do.call(rbind, simpsons_writers_1),
do.call(rbind, simpsons_writers_2))

ratings <- list()
episodes <- list()

for(i in 1:3) {
ratings[[i]] <- page %>%
html_nodes(".col-imdb-rating") %>%
html_text()
episodes[[i]] <- page %>%
html_nodes(".col-title") %>%
html_nodes("a") %>%
html_text()
}

all_episodes <- unlist(episodes)
all_episodes <- all_episodes[seq(2, length(all_episodes), by = 2)]
all_ratings <- as.numeric(unlist(ratings))

ratings_df <- data.frame(imdb_title = all_episodes[1:600],
wiki_title = simpsons_writers$Title[1:600], rating = all_ratings[1:600], writer = simpsons_writers$Written by[1:600])


Now to cleaning these data up. There’s not really a principled way of doing this, I just scanned the data for obvious issues and then used regex to clean up any errors I spotted. The aim is to get the data into a format where each row has an individual writer involved in an episode and the corresponding rating.

# Some rows don't have spaces between names
# Identifying cases where two lower case letters are followed by an upper case
# And placing a space before the upper case letter
# Looking for two lower case letters to avoid names with 'Mc'
ratings_df$writer <- gsub("([a-z]{2,})([A-Z])", "\\1, \\2", ratings_df$writer)
# Removing some additional non-name text as well as 'and' and '&'
ratings_df$writer <- gsub("and|&|Teleplay by.*:|Story by.*:", ", ", ratings_df$writer)
# Removing footnote tags
ratings_df$writer <- gsub("\$.*\$", "", ratings_df$writer)

# Separating the writers
ind_writers <- sapply(ratings_df$writer, function(x) strsplit(x, ",")) # Find how many writers were involved on each episode no_writers <- as.numeric(sapply(ind_writers, length)) row_index <- rep(1:600, times = no_writers) # Duplicating episodes which have >1 writer and giving each writer a row ratings_df <- ratings_df[row_index, ] ratings_df$ind_writer <- unlist(ind_writers)

# Cleaning the individual writers text
# Removing any leading or trailing whitespace
ratings_df$ind_writer <- gsub("^[ ](.+)", "\\1", ratings_df$ind_writer)
ratings_df$ind_writer <- gsub("[ ]$", "\\1", ratings_df$ind_writer) # A few of the writers went by pseudonyms for some episodes ratings_df$ind_writer[ratings_df$ind_writer == "Penny Wise"] <- "Jon Vitti" ratings_df$ind_writer[ratings_df$ind_writer == "Pound Foolish"] <- "David Silverman" ratings_df$ind_writer[ratings_df$ind_writer == "Lawrence Talbot"] <- "Dana Gould"  Finally, I just used dplyr to get the mean episode ratings per writer. # Remove cases where I've wrongly identified multiple writers ratings_df <- ratings_df[ratings_df$ind_writer != "", ]

# Recode writer to "Other" if involved in <10 episodes
ratings_df <- ratings_df %>%
group_by(ind_writer) %>%
mutate(inc_writer = ifelse(n() >= 10, ind_writer, "Other"))
# Get the average episode ratings for writers with over ten writing credits
ratings_df <- ratings_df %>%
group_by(inc_writer) %>%
mutate(avg_rating = mean(rating))