Gaming Video Retention Benchmarks Do Not Exist

There is no published, measured retention benchmark for gaming videos. YouTube does not publish one, and the tables that circulate assigning gaming a target percentage are either unsourced or aggregated from surveys and secondary reports, which is not the same thing as a measurement.

That absence is the finding. The percentages may work as private rules of thumb, but you cannot treat them as measurements of gaming audiences. The public evidence consists of one channel disclosing its own analytics, one leaked creator handbook, academic work outside gaming, and adjacent studies about gaming supply, video length, and viewer intent.

The practical substitute is your own channel median. Compare each upload with your last 10 videos of similar length and format, then read the shape of the audience retention curve. That comparison measures your audience, your packaging, and the promise your video made.

The benchmark tables have no visible dataset

Search for a good gaming retention rate and you will find precise ranges. Some pages place gaming near the low end of YouTube. Others claim gaming videos should reach 60-80% average percentage viewed. The pages reviewed for this research did not disclose channel lists, analytics exports, sample sizes, collection dates, or rules for separating one gaming format from another. Some contradicted each other.

A suggested target may still work as a private rule of thumb. Without those fields, readers cannot audit the number or know whether it describes Shorts, guides, livestream archives, or edited essays. Calling it a benchmark gives it more authority than the published method supports.

YouTube's own audience retention documentation does not fill the gap. It defines the Intro metric as the percentage of viewers still watching after the first 30 seconds and explains that videos tend to taper during playback. It publishes no category percentage for gaming.

Our GTA 6 creator playbook flags this gap. The narrower question here is what evidence a gaming creator can defend.

Gaming contains formats that should not share one score

Average percentage viewed divides average view duration by video length. That makes length part of the score before topic, editing, or audience behavior enters the comparison.

A search guide near the 14 minute 50 second average found in first-page YouTube results asks viewers to solve a task. A Summoning Salt documentary can run from 45 minutes to more than 2 hours and asks viewers to follow a story. A no-commentary longplay can run up to 8 hours and may function as story viewing, reference material, or something a viewer resumes later. All three count as gaming.

Traffic source changes the job. A search viewer may leave after getting an answer. A returning viewer may open a long essay for the creator. A suggested-viewer click depends on a title and thumbnail promise that the opening must prove. One niche average collapses those decisions.

Length and format can vary more inside gaming than between gaming and another broad category. Any useful benchmark would have to separate at least long-form from Shorts, search utility from entertainment, and edited videos from livestream archives. No public study has done that work.

The real evidence comes with large limitations

The useful sources do not form a gaming benchmark. They give us anchors, boundary conditions, and reasons to distrust confident universal targets.

The vidIQ disclosure is valuable because the company states the channel, metric, and view base. A large, competent channel sitting at 30.3% average percentage viewed should make you skeptical of unsourced claims that long-form gaming needs 50-70%.

The MrBeast figure shows that a production team known for retention can call a first-minute loss of about 35% reasonably good. It does not set a target for your gaming channel.

The 2025 arXiv paper supplies rare public curve data, but its sample covers energy-topic videos. Its roughly 75% brief-viewer finding cannot support a gaming benchmark.

Pex found heavy gaming supply, while Pew found longer gaming videos among popular channels. Those facts describe a crowded category with broad duration. Neither source says what percentage viewers should finish.

Average percentage viewed hides the failure you need to fix

One percentage cannot tell you where viewers left. The same average can come from an opening cliff or a later drop caused by a delayed answer. Those videos need different edits.

Read average view duration, average percentage viewed, and the curve together. The distinction between average percentage viewed and audience retention matters because one compresses the session into a score while the other preserves timing.

Start with your opening. YouTube gives the first 30 seconds a named Intro metric because an early mismatch between the click and the video deserves separate attention. Then inspect sharp dips, spikes, and the slope between them. Our guide to reading a YouTube retention graph explains what each shape can mean without pretending every dip has one cause.

Use your own median as the reference line. Take the last 10 uploads with similar length, format, and traffic intent. Compare a guide with guides and an essay with essays. The median keeps one breakout or one failed experiment from setting the standard for the rest.

A long video can produce more watch time with a lower percentage viewed. A brief video can show the reverse. Watch time, retention, and click-through rate answer different questions.

Each gaming format creates a different retention mechanism

This section is inference, not measurement. No public dataset establishes format-level gaming benchmarks, so the claims below describe how viewers use each format and what part of the curve deserves attention.

Guides should deliver the task without wasting the click

Google and Ipsos found that 74% of YouTube gamers watch to get better at games. A guide viewer arrives with a job: find an item, beat a boss, or understand a system. The opening should confirm that the video solves that job. A drop after the answer may show completion rather than dissatisfaction.

Judge a guide against other guides aimed at similar queries. Look for abandonment before the answer, replay spikes around a difficult step, and comments that reveal missing context. Search performance and useful watch time belong beside the curve.

Let us plays depend on continuity and attachment

A commentary let us play asks viewers to follow both the game and the creator. Episode position, returning-viewer behavior, and the strength of the ongoing story can shape the curve before editing quality enters the picture.

Creators often say the first walkthrough episode takes the largest audience and later parts decay. The pattern is visible on public channel pages, but no formal study in the research set measured it. Treat it as plausible folklore. Compare middle episodes with other middle episodes rather than with the series premiere.

Essays need progression across a longer promise

Gaming essays and documentaries can hold attention through argument, chronology, or unresolved questions. Summoning Salt uses world-record progression as a story spine, with each record creating the next question. The mechanism gives a long video repeated reasons to continue.

A lower average percentage viewed can still accompany substantial watch time on a long essay. Inspect where each section hands viewers to the next one. Compare essays within a similar duration band and resist using a guide target against a documentary.

No-commentary videos serve immersion

No-commentary longplays remove the personality hook that much creator advice treats as mandatory. GamesRadar has described the format as story consumption and reported videos lasting up to 8 hours. No public retention dataset shows how those audiences behave.

The useful comparison set contains other no-commentary videos of similar length and game type. Seek spikes, long flat sections, and return behavior may reflect how viewers use a longplay as much as how well it holds a continuous session. That reading remains inference until someone publishes the analytics.

A real benchmark would require analytics exports

A defensible study would need creator-supplied YouTube Studio exports rather than public view counts. Researchers would have to separate Shorts, edited long-form videos, livestream archives, and premieres. They would also need format labels for guides, commentary playthroughs, essays, challenge runs, and no-commentary videos.

Length bands, traffic sources, video age, channel size, and returning-viewer share would need separate treatment. The study should publish medians, distributions, and sample sizes. Its method would also need rules for deleted videos, paid traffic, and packaging changes after publication.

No one has published that dataset. More precisely, our research found no public study with those fields as of 27 August 2026. YouTube and creator-tool companies may hold private data that could answer parts of the question, but readers cannot inspect data that stays private.

Your channel median is the benchmark you can defend

You do not need a universal gaming percentage to make the next video better. You need a stable comparison set and a curve that tells you where your own viewers changed their minds.

Group the last 10 comparable uploads. Record their median Intro retention, average view duration, and average percentage viewed. Mark the video that beats the median, then inspect the curve for the moment it earned the difference. Repeat the same comparison after the next upload.

Your own median is the only benchmark built from your format, length, audience, and traffic mix. A public gaming benchmark may become useful if someone releases the method and data behind it. Until then, a precise unsourced table offers certainty without evidence.

If you want to check whether a script earns each section before you record, run it through PrePublish. It gives you a second read on the opening, structure, and promise without inventing a retention target.