So, my original post about the Rotten Tomatoes score for The Odyssey on KiA went viral, which has been a bit surreal to witness. Since it struck such a cultural nerve, I thought I'd do a quick follow-up with some further findings.
The Pre-2019 vs. Post-2019 Divide
Here's a sampling of well-known movies, ranked from best to worst using the "pull" method (note: this is the scoring method that Rotten Tomatoes used prior to 2019).
| Movie Name |
Pull Audience Score (Reliable) |
Push Audience Score (Unreliable) |
| Fight Club |
96% |
N/A (Pre-2019) |
| Fellowship of the Ring |
95% |
N/A (Pre-2019) |
| Inception |
91% |
N/A (Pre-2019) |
| Gladiator |
87% |
N/A (Pre-2019) |
| The Matrix |
85% |
N/A (Pre-2019) |
| Ant-Man and the Wasp: Quantumania |
69% |
81% |
| The Woman King |
62% |
99% |
| Star Wars: The Rise of Skywalker |
62% |
86% |
| One Battle After Another |
60% |
85% |
| The Marvels |
59% |
79% |
| The Odyssey |
56% |
97% |
| The Little Mermaid (2023) |
44% |
93% |
This chart lays bare the problem with the default "push" (verified) scores now used on Rotten Tomatoes, and highlights how the crowdsourced "pull" (unverified) scores do a much better job representing reality.
Once the inflated push data is removed, a remarkable sense of sanity returns to the numbers.
The North American Bias Bombshell
An insightful comment from /u/zincovit revealed an unexpected new bombshell: the default Popcornmeter only includes North American votes. Rotten Tomatoes does not currently verify user accounts or ticket purchases outside North America.
This effectively turns the entire international moviegoing audience into second-class citizens. The primary Popcornmeter is functionally restricted to a domestic Fandango echo chamber.
It is the height of hypocrisy for defenders of these corporate aggregators to posture as champions of global inclusion while actively backing a metric system that structurally disenfranchises the rest of the world.
The JSON Odyssey: Moderation Shenanigans
I've been closely tracking the raw JSON data for The Odyssey since my first post went live. Immediately after the initial thread blew up, the unverified score jumped from 56% to 62% within half a day due to a wave of activity. Since then, the pattern of updates confirms that RT releases unverified ratings in large, reconciled batch flushes rather than streaming them live (which matches what I predicted).
Even more fascinating is what the backend data reveals about RT's moderation pipeline. By comparing sequential JSON snapshots, I have evidence that unverified reviews are routinely purged after going live.
While the net removals are small (~10 reviews over three days), it confirms that backend sweeps actively delete full review objects in the background. Furthermore, this analytical data suggests that reviews submitted with text commentary pass initial automated filters faster than star-only submissions, which are frequently held "under review". I would be interested to see this tested to confirm or refute this hypothesis.
The Codification of the Pull vs. Push Argument
My inbox blew up after the viral post. First off, thanks to everyone who offered support, additional data, or shared their perspective!
The most common objection I received can be summed up in a single sentence: "Only people who have seen the movie can have an opinion on its quality."
On the surface, "only movie watchers can review it" sounds logical in principle. In practice, however, it fails completely. The only practical way to make a true "watcher-only" scoring system work fairly would be to gather a fully random global sample of at minimum 1,000 people, sit them down to watch the movie, give them three days to reflect, and then collect their scores.
Without that impossible setup, relying purely on self-selected ticket purchasers causes every single movie to sit comfortably at 90%+, rendering the metric useless.
The Case for the Pull Methodology
The pull method (where users independently seek out the page, log in, and leave a review) is not perfect. It biases toward extreme reactions and requires filtering against spam or coordinated campaigns. Yet, despite those challenges, it consistently yields a far more accurate reflection of public sentiment.
In the end, including unverified voices is an essential input for a true crowdsourced score. When properly filtered against spam and manipulation via robust platform safeguards, it is pull-based metrics that cut through sentiment inflation to deliver a realistic index of actual public sentiment across a wide range of films.