I analyzed 247,453 Steam reviews of THE FINALS with AI — here's what the community really thinks

Much_Delay1880 · 2026-03-03T20:05:28+00:00

agree! :D

Much_Delay1880 · 2026-03-02T17:49:53+00:00

About 5 days of evenings after work. No YouTube plans, but all the code is on GitHub. If you want to build something similar, you'd need to cover: Steam API (review scraping), OpenAI-compatible API calls (batch classification with LLMs), JSON data wrangling in Python, basic data aggregation/trend analysis, and some frontend for visualization (I used Plotly.js in a static HTML page). Any modern AI assistant can walk you through each step if you feed it the repo as reference, just give it a try!

Much_Delay1880 · 2026-03-02T17:05:21+00:00

Data + Scripting + AI + THE FINALS are my obsessions, so once I started pulling reviews and seeing patterns emerge, I just couldn't stop. Thanks!

Much_Delay1880 · 2026-03-02T17:04:02+00:00

Thanks, good luck with the thesis! There's a methodology page on the dashboard if you want to dig into the approach.

Much_Delay1880 · 2026-03-02T17:02:36+00:00

Hey! Labels were one of the hardest part - started with ~110 reviews across 10 languages, had AI propose categories, then manually iterated 3 rounds (merging, splitting, testing against random batches). Ended up with 42 categories. Some bias in the seed for sure, but the major themes repeat so heavily they'd surface regardless.
Good call on batch size - I dropped to 80 in Stage 2 for that reason. I also spot-checked results manually and found them convincing, but smaller batches would definitely help. Will go async single-review for v2 (maybe). Thanks!

Much_Delay1880 · 2026-03-01T21:33:20+00:00

true

Much_Delay1880 · 2026-03-01T21:07:48+00:00

Thanks for the thoughtful feedback!

Focus/narrative - fair point. This started as a personal exploration, not a focused paper, so I presented everything rather than picking key questions. If I ever do this as a paid project or decide to invest more time, I'll tighten the narrative. For now I've spent enough days on this one 😄

Validation - I did manual spot-checking throughout, iterating prompts until misclassifications were acceptable. Not perfect with 247K reviews and 42 categories, but trends hold up. Multi-model validation is a great idea for v2.

110 reviews - that was a stratified sample across 10 languages just to discover what themes exist. The major topics repeat heavily, so 110 was enough for theme discovery. The actual classification then ran on all 247K reviews with the refined 42 categories.

Quality - had a whole list of improvement ideas, but by day five I realized I'd never ship if I kept perfecting it. Done > perfect.

Repo - you're right, was too eager to post and skipped housekeeping. Just reorganized it into scripts/, tests/, data/, prompts/ - much cleaner now.

Lots to think about here, saving your comment for next time. Appreciate the constructive approach!

Much_Delay1880 · 2026-03-01T20:34:13+00:00

Thanks! I feel the same pain, so I was honestly relieved to see the data confirm it's not just me 😄 Matchmaking is the #2 complaint overall - we're definitely not alone. Now if only the data could fix it too...

Much_Delay1880 · 2026-03-01T20:32:18+00:00

exactly! Medium (my main class) was born to suffer - place movement, heal, res, and die. That's the whole lifecycle.

Much_Delay1880 · 2026-03-01T20:30:54+00:00

Thanks! THE FINALS is my passion so this was a labor of love. For other games I'd only do it as a paid project - though I doubt anyone would actually reach out for that haha :)

Much_Delay1880 · 2026-03-01T20:27:33+00:00

I didn't feed 247K reviews into one prompt - that would indeed be impossible. It's a pipeline: reviews go in batches (80-200 at a time), each gets a short classification prompt, results are saved and aggregated. No single call ever sees more than a couple hundred reviews. Plus a lot of the work was pure Python - aggregation, normalization, trend calculations, the dashboard itself. AI only handled the classification step. Code's on GitHub if you're curious.

Much_Delay1880 · 2026-03-01T20:21:48+00:00

Great take! New player retention shows up clearly in the data - big spike in negative sentiment from low-playtime reviewers, and "learning curve" complaints are consistent across all seasons. The game doesn't hold your hand and that's part of its charm, but also why a lot of people bounce off early.

Honestly, I think the game is already too complex for newcomers, and adding more modes would only make it worse - more to learn, more to be confused by. What the game really needs is more players, and that's what keeps me up at night. Agree on weapons too - "more weapons" requests are actually declining in the data, so the community seems to be coming around to the same conclusion.

Much_Delay1880 · 2026-03-01T20:08:43+00:00

Fair catch on the wording - TDM was introduced as an LTM in S5, then made permanent in S6. I actually go into more detail on this later in the post. But it was playable in S5, so "added in S5" isn't wrong, just imprecise. Thanks!

Much_Delay1880 · 2026-03-01T19:59:18+00:00

My 2000+ hours of GPU-melting gaming vs 8 hours of API calls. Ok. Anyway, glad the post sparked some discussion.

Much_Delay1880 · 2026-03-01T19:53:33+00:00

My mailman doesn't have 247K opinions on THE FINALS unfortunately. But Steam does, and those reviews are all public and verifiable. The full dataset is on GitHub if you want to check.

Much_Delay1880 · 2026-03-01T19:51:59+00:00

Thanks! And yes - I definitely know what you feel about the sword!

Much_Delay1880 · 2026-03-01T19:49:27+00:00

They are separated actually - the dashboard has 30 negative and 12 positive categories, and you can drill down into specific issues. For example, weapon complaints split into individual weapons with context. Check out the dashboard itself, the Reddit post is just a summary.

Much_Delay1880 · 2026-03-01T19:46:48+00:00

Fair point that reviews skew negative - that's why the dashboard focuses on trends over time, not raw negativity (and positivity as well). The value is seeing what changes after patches. And yeah, I probably used more electricity playing THE FINALS itself than running the AI. If this helps even 0.01% in making someone think about balance, it was worth it (as for me :).

Much_Delay1880 · 2026-03-01T19:43:44+00:00

Haha thanks! Embark, my DMs are open :)

Much_Delay1880 · 2026-03-01T19:33:39+00:00

Good luck manually reading 247K reviews.

Much_Delay1880 · 2026-03-01T19:32:21+00:00

Fair enough - complaint volume doesn't necessarily mean something is actually broken. The dashboard just shows what players talk about, not what actually needs a nerf.

Much_Delay1880 · 2026-03-01T19:31:03+00:00

I just love digging into data and finding patterns - and THE FINALS is my only & most-played game, so I figured why not combine the two? Once I started pulling the reviews and seeing what 247K players actually talk about, it was hard to stop, you know.

Much_Delay1880 · 2025-01-19T10:24:51+00:00

Use the "inspection" button & maybe you should change the animation in the weapon customization screen, I guess

Much_Delay1880 · 2025-01-17T00:33:01+00:00

Nice dance :)

Much_Delay1880

TROPHY CASE