Data and download

Take it all

The tables

The other tables

How the files are shaped

One row is one thing: a source, a claim, a trend, a game. Where a row carries a list of other things, that list gets a file of its own rather than a cell with five links glued into it. That is why the further reading on a trend and the example games in a genre are separate tables, each keyed by the name of the thing they belong to.

A list of plain words stays in its cell. Markets and languages are written into one cell with a semicolon and a space between them, because splitting three tokens into a table of their own helps nobody.

CSV is UTF-8 and RFC 4180, quoted where a value needs it. Plenty of these rows carry Japanese, Korean, Chinese and Arabic, so if your spreadsheet opens one and shows you a fence of question marks, it has guessed the encoding. The workbook above is the quicker fix.

JSON is the same data with the nesting left in. There is nothing in the JSON that is not in the CSVs; it just has not been flattened, which is what you want if you are feeding this to code or to a model.

An empty cell means the field was not collected for that kind of row, not that the answer is nothing. Cost is asked of data platforms, where the price decides whether you can use the thing at all. ISBN is asked of books. Neither is missing from a subreddit.

There is no ID column. Rows are identified by name, and the row order is export order, which is not a ranking of anything by anyone. If you need keys that survive the next pass, build them yourself from the name and the link.

Fields in the source table

name

What the source is called. The closest thing to a key this table has. Two things can share a name, in which case the link settles it.

group

One of the six doors of the site: Data, Institutions, Press, Media, People, Communities. Every row has exactly one.

medium

What kind of thing it is, from one list of thirteen values that reads across the whole table: news outlet, organisation, forum or community, video channel, data tool, podcast, person, book or paper, company disclosure, report or document, newsletter, research firm, link list.

format

The finer classification, read inside its group. A Press row is a national daily or a trade outlet; a Data row is an analytics platform or a corporate filing. Every value, and how many rows carry it, is in the vocabulary file.

what_it_lets_you_find_out

What you can actually get from it, written after reading it, including the limits worth knowing before you cite it. The longest field in the table and the reason the table exists.

markets

Which markets it covers, as codes. Global means it covers the lot. Not market specific means market is not the axis the source works on.

language

The language or languages you will be reading it in. Not a claim about translation being available.

cost

Free, Paid, or a mix. Collected on data platforms alone, where price decides whether the thing is usable at all, so it is empty across most of the table.

link

Where to go. One address, and the front door rather than a deep link, because deep links rot first.

extra_links

Second and third addresses for rows that need them. Empty on every row today. It stays in the file because it is part of the shape rather than a promise.

owner

Who owns or runs it, where that is knowable and matters. Filled on roughly three rows in five.

ownership_note

Where the ownership changes how you should read the source: a platform that absorbed its rival, an outlet owned by the group it reports on, a body funded by the companies it represents.

caveat

What to watch for. A coverage gap, a method limit, a paywall across the part you actually wanted.

beat

On people, what they cover.

where_they_post

On people, the platform you will actually read them on, which is frequently not where the link goes.

year

Publication year, on books and papers.

isbn

Thirteen digits, no hyphens, on books that have one.

audience

Who a media source is for. On video, podcast and book rows.

Fields everywhere else

Markets

One record per market. sections holds the claims, grouped under Market size, Shape, Press structure, Venues, Where the data lives, Unique to this market and Standing. Each claim carries its source and its link, plus a kind of Narrative or Card entry that says where it renders on the site rather than anything about the claim itself. player_population holds the figure as the source published it, a plain number beside it, the measure and definition stating who exactly was counted, the year, and where it came from. Nine of the ten markets have one; MENA has no comparable figure and so has none. Read the definitions before you chart anything: these figures are not comparable across markets, and treating them as if they were is how bad slides get made.

Trends

stage is Emerging, Dominant, Perennial or Receding. category sorts them into six groups. what_it_is carries the figures, why_it_matters is the short form, where_to_follow names who is covering it, and as_of is when it was last looked at. The reading file types every link as Reporting, Analysis, Data, Primary, Community or Research.

Platforms and genres

Platforms carry a category, an owner and the markets they matter in. Genres carry a segment saying where the genre lives, a definition, its subgenres, and local_terms: the words used in Chinese, Korean and Japanese, which is the field that saves you when a vendor's taxonomy and yours disagree. The example games file names each game and says why it is there.

Searching tips

tip is the technique, how is the thing to type, example is a query you can paste as it stands, why explains what it surfaces. markets says where it applies.

Vocabulary

facet is the field, value is one of the values it takes, rows is how many rows carry it. within_group is filled only for format, which is read inside a group and nowhere else.

What to tell your LLM

Attach the file. Do not paste it. A model handed sources.csv as an attachment can filter it, count it and quote it. A model handed 813 rows in a chat window starts summarising them, and summarising is where invented rows come from.

The prompts below all do the same two things: they name the file and the columns, and they say what the model must not do. That second half is the half that matters. Left alone a model will rank these sources, fill an empty cell with something plausible, or quietly refresh a 2026 figure from memory, and nothing in the file gives it a way to notice. Take one, change the market or the question, and go.

• Start here, every time

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  I have attached files from Delightful's Game Research Starter Pack, a directory of where to research the video games industry. sources.csv holds 813 sources, each with a description of what it lets you find out, who owns it, what it costs and which markets it covers. Treat it as a map of where to look, not as a store of facts. Every source was read before it was described, but nothing the sources themselves claim has been checked, and nothing in the file is ranked or scored, so row order means nothing. When you answer, name the rows you used and give me the link from the row. If the file does not cover what I asked, say so instead of filling the gap from what you already know.

• Build a reading list for one market

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  From sources.csv, give me everything covering Japan: the rows whose markets column contains JP. Group them by the group column, and inside each group put the rows whose language is Japanese first. Return a table of name, what it lets you find out, and link. Then tell me which languages I will need, and flag any group holding fewer than five rows, because that is thin coverage in this directory rather than a fact about Japan.

• Find who publishes a number

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  I need to state how much was spent on mobile games in Germany last year, and I need something citable. Using sources.csv, list every row that could plausibly publish that figure, starting with the Data and Institutions groups. For each one, tell me what the caveat and ownership_note columns say and whether cost is Free, then order them by how likely I am to get the number without a subscription. Do not give me the figure itself. I am going to go and read it.

• Shortlist the free tools

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  From sources.csv, take only the rows where group is Data and cost is Free or names a free tier. For each, tell me what it measures, what it explicitly excludes, and which of them draw on the same underlying data so I do not check one number twice and think I have confirmed it. The what_it_lets_you_find_out column states the known limits. Use those rather than your own impression of these tools.

• Write a trend brief

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  Using trends.csv and trend-reading.csv, joined on the trend name, write a one-page brief on the trends whose stage is Dominant or Emerging and whose markets include Korea or Japan. For each one, quote the figures in what_it_is exactly as written, add the why_it_matters line, and pick the two most useful links from the reading file, naming their type. Do not add a trend that is not in the file, and do not update any figure from your own knowledge. The as_of column tells you how fresh each row is; say so where it is old.

• Search in the local language

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  From genres.csv, pull the local_terms column for shooters, role-playing games and puzzle games, and give me the Chinese, Korean and Japanese terms with a romanisation. Then, using the how and example columns of searching-tips.csv, turn each term into two or three queries I can paste straight into a search engine to find market coverage rather than store pages. Keep the local script in the queries.

• Check the coverage before you claim anything

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  Using vocabulary.csv, tell me how many rows this directory holds per market and per language. Then name the markets where the count is low enough that an absence in this data says more about the directory than about the market itself. I am about to present findings from these files and I want to know where I would be arguing from a gap.

Licence

Creative Commons Attribution 4.0. Use it, cut it up, publish from it, build something you charge for. The one condition is credit: name this site, link the licence, and say if you changed something.

The licence covers the data in these files. It does not cover what the rows point at. The reporting, figures, artwork and writing at the far end of every link belong to whoever made them, and nothing here hands you any part of that.

Working with the data