Data Exploration - Rotten Tomatoes versus the Academy

Overview

This is my third blog post about Oscar movies and ratings. In this blog we’ll be exploring and visualizing the dataset I curated in my last blog of Oscar movies and Rotten Tomato scores.

While there is some bias and personal preference when it comes to picking out the best movies, we know that it’s not completely subjective. Many people can agree that certain movies are terrible and certain movies are great. Just like how “Surf’s Up” (2007) is simply a better penguin movie than “Happy Feet” (2006), there seem to be some qualities that make one movie better than another.

That being said, you would think that Rotten Tomato Critics and the Academy would be aligned on the movies they claim to be the best; if a movie were to get above 90% on Rotten Tomatoes, it’s probably safe to assume that movie would get some nominations at the Oscars.

Well, suprise! That’s not really the case. One of the biggest surprises from the Oscar nominations this year was that Mia Goth received no nominations for her performance in “Pearl” (2022). It got a 92% on Rotten Tomatoes, yet didn’t get a single nomination in the 2023 Oscars Ceremony.

Look at how scary this face is. You’re really not going to give her a nomination, @Academy? Be real.

The Data

We’ll be exploring the relationships between the variables in the movies dataset I created in the last blog. This combined an Oscar’s dataset with ratings scraped from the Rotten Tomatoes website. That blog is linked here if you want to check it out.

The dataset looks something like this:

Ceremony: the Oscars ceremony number
Name: the studio or production company
film: the movie title
winner: True or False if the movie won best picture
Tomato Score: the Rotten Tomato score (0.0-1.0)
Year: the year the film came out
Critic Review: the review from Rotten Tomatoes
Nomination Count: the count of nominations received in a ceremony

Visualizing

The first thing I wanted to explore was the relationship between Oscar nominations and Rotten Tomato Score. Each point on this scatter plot represents a movie in our dataset (all nominations for best picture). It shows the number of nominations received in any category in one award show on the y-axis. This is plotted against their Rotten Tomato Score out of 100% on the x-axis. Whether or not a movie won the best picture award is indicated by the color.

It’s not surprising that most of the points hover between the 80%-100% mark. I was suprised by the way the orange points (winners of best picture) were dispersed among the blue points. You’d expect best picture winners to be clustered towards the top, but they seem to be pretty evenly distributed throughout the blue points.

This visual shows only the winners, with a few interesting outliers labeled.

“Coda” won best picture in 2022, yet received an abnormally low number of total nominations.
“Out of Africa” won best picture at the 1986 Oscars, yet was given a low Rotten Tomatoes score of 61%.
“The Greatest Show on Earth” won best picture in 1953, yet got the lowest Rotten Tomatoes score of any winner in this dataset: 49%.

When I first looked at the points for “Out of Africa” and “The Greatest Show on Earth”, I thought that the discrepancy between the Academy and Rotten Tomatoes could’ve been due to how old these movies are. It would make sense that movie quality and criteria for good movies has changed over time.

To test this theory, I created the plot below that shows the average Tomato Score for winners over the years:

We can see where “The Greatest Show on Earth” and “Out of Africa” are dragging the average down around 1953 and 1986. Besides that, there isn’t a very obvious increase of average Tomato Scores happening throughout the years. In fact, one of the most consistently high average score time periods looks to be between 1970-1980.

This made me interested to see where the highest Rotten Tomato Scores were given over time. This plot shows every Rotten Tomato Score in this dataset given over 97% and the year it was given in.

In this dataset, there hasn’t been a nomination that had 100% on Rotten Tomatoes since 1971. It makes me wonder if movies aren’t as “good” as they used to be, if the Rotten Tomato criteria has become more strict, or maybe “the best” according to the Oscars versus Rotten Tomatoes has grown more different from each other over time.

This last visual shows a spread of the nominees versus the winners plotted with their Tomatoes score.

The mean for winners is a little higher for nominees, which I would expect. It’s interesting that the maximum Tomato Score for nominees is higher than the maximum for winners. In this dataset, no Oscar best picture winner has a 100% on Rotten Tomatoes.

Conclusion

To wrap up, I found that the Rotten Tomatoes critics and the Academy like to have their own opinions on which movies are the best of the best. Though average Rotten Tomatoes scores for best picture winners oscilate, they have remained relatively level over the years. If you have any questions, comments, or want to talk about “Surf’s Up”, feel free to leave a comment below.

The repository containing the code I used to make these visuals can be found here.