A “whale” is a spending category, not a personality type or a verdict about someone’s wealth or mental health. In the studies that use the term, it usually means the small group of players who account for a large share of a game’s in-game purchases, and the way that group is defined changes from study to study. Research has found that heavy spending is concentrated in some populations and is associated with gaming and gambling problem measures, but it has not shown that high spenders are typically rich, and it has not shown that every paying player is a problem player. This article explains what the label measures, what the evidence does and does not establish, and why we treat paying players of social games as gamers.
What “whale” actually refers to
“Whale” has no fixed cutoff. Each study sets its own line for what counts as heavy spending, usually by ranking paying players and taking the top slice, or by setting a monthly spending figure. Two studies with the most detailed definitions illustrate how far apart these choices can be:
- Top 5% by monthly spend (loot boxes, 2021). Close and colleagues treated the top 5% of loot-box spenders, defined as those spending more than $100 per month, as the high-spending group.
- Top 10% over 12 months (all in-game purchases, 2026). A Frontiers in Public Health study of adolescents in Austria defined heavy spenders as the top 10% of paying participants by expenditure over the preceding 12 months.
Because the cutoffs differ, a “whale” in one study is not directly comparable to a “whale” in another. When you read the term, the first question to ask is what the study counted as spending and who it counted as paying.
How concentrated is heavy spending?
Within the samples these studies examined, spending is heavily concentrated. In the 2021 secondary analysis of open-access survey data from 7,767 loot-box purchasers, the top 5% of spenders accounted for half of loot-box revenue in that dataset. In the Austrian adolescent study, the top 10% of paying participants accounted for 61.4% of reported in-game spending.
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These two figures should not be combined into an industry-wide estimate. They come from different samples, different purchase categories (loot boxes in one case, all in-game purchases in the other), different age groups and different time windows. Neither source establishes what share of total game revenue comes from whales across the market, and the current evidence reviewed here does not provide a global figure. Older market-size estimates that circulate in secondary coverage are not a substitute for that.
Comparing the studies
The table below sets out the key differences. Where a study summary does not state a detail, the cell says so rather than filling it in.
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| Study | Players measured | What counts as spending | Heavy-spender definition | Headline finding | Scope limit |
|---|---|---|---|---|---|
| Close et al., Addictive Behaviors, June 2021 (PubMed record) | 7,767 loot-box purchasers in open-access survey data; secondary analysis | Loot-box purchases, self-reported | Top 5% of spenders, more than $100 per month | Top 5% accounted for half of loot-box revenue in the dataset; no significant correlation between loot-box spend and earnings (ρ = 0.02, p = .10); positive correlation with problem-gambling measures | Country not stated in the source summary; loot boxes only, not all purchases |
| Frontiers in Public Health, 2026 (study article) | Adolescents in Austria | In-game expenditure, including microtransactions | Top 10% of paying participants over the past 12 months | Top 10% accounted for 61.4% of in-game expenditure; no significant difference in measured family affluence between heavy and casual spenders; higher spending associated with gaming-disorder and gambling-disorder measures | Adolescent sample; associations, not diagnoses |
| Gainsbury, King, Russell and Delfabbro, Journal of Behavioral Addictions, 2016 (PMC article) | 521 social casino game players in an Australian online survey | Purchases within social casino games | Not defined as a whale threshold; paying players compared with non-paying players | Paying players reported higher play frequency and engagement, and placed more weight on social interaction as a motive | Australian sample, collected 2016; not a current prevalence or market-size estimate |
Are whales wealthy players?
The simple assumption is that heavy spending reflects deep pockets. The studies above do not support that as a general explanation. Close and colleagues found no significant correlation between loot-box spend and earnings in their data. In their words, “there was no significant correlation between loot box spend and earnings ρ = 0.02, p = .10.” The Austrian study, for its part, found no significant difference in measured family affluence between heavy and casual spenders.
These results weaken the idea that high spending is simply a matter of wealth. They do not, however, establish the finances of every high spender. The 2021 earnings figures were self-reported, and the Austrian study measured family affluence rather than individual income. Neither study can tell you what a particular player can afford.
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Are whales problem gamblers?
Here the evidence is more concerning, but it still needs careful reading. The 2021 analysis reported a positive correlation between loot-box spending and problem-gambling measures. The 2026 Austrian adolescent study found that higher spending was associated with gaming-disorder and gambling-disorder measures.
An association at group level is not a diagnosis, and it is not evidence that spending causes problems. Some heavy spenders may show few or no problem signs, and some problem players may spend little. Use the findings to describe what was measured in a particular sample. Do not use them to label an individual player.
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What social casino players tell us
Social casino games, which mimic casino gameplay with virtual currency, are often dismissed as harmless or as something other than “real” gaming. The 2016 Australian survey complicates that picture. Among 521 players, the paying group reported higher play frequency and engagement. The authors wrote that paying players “emphasized social interaction more strongly as a motivation for playing.” The study also described more than one paying group:
- Players who bought credits to avoid waiting for them to refill, or to give gifts to others.
- Less frequent high spenders who sought more entertainment value from their purchases.
The point is not that social casino players are all the same. It is that paying is not a single motive, and the people who pay are not uniformly passive or uniformly compulsive.
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Why we treat social gamers as gamers
We use “just gamers” as an editorial position, not as a finding from the studies. The evidence describes how often people play, how much they engage, what they spend and why they say they play. It does not establish how social casino players identify themselves, and the surveys did not ask whether they call themselves gamers or prefer any particular label.
That gap matters in both directions. Calling social game players “casual” or “not real gamers” has no support in these studies, and the same is true of calling them all problem players. A player who buys credits to skip a wait, shares gifts with friends, or plays a few times a week for the entertainment is a gamer in the ordinary sense of the word. The studies support treating them that way, and they show that the motives behind spending are varied.
Using the term responsibly
- Say “heavy spender” or “whale” as a reported category, and name the study’s definition where you can.
- Specify whether the finding concerns loot boxes, all in-game purchases or social casino purchases.
- Describe findings as associations or distributions, not diagnoses or causes.
- Do not describe a player as wealthy, vulnerable or addicted because they spend heavily.
- Check the date and country before applying a finding to today’s market.
What the current evidence does not settle
Several questions remain open. The studies reviewed here do not give a current global share of game revenue from whales. They do not establish how many heavy spenders develop problems over time, since the measures are cross-sectional. They also do not show how different game designs change spending patterns, because the purchase mechanics and populations differ across the samples. Until more research addresses these points, the most accurate position is the narrow one: heavy spending is concentrated in some samples, it is associated with problem-gambling and gaming-disorder measures in those samples, and it is not reliably explained by wealth.
Whether the term “whale” is useful depends on how carefully it is used. As a label for a measured spending group, it helps describe where money comes from in a game. As a label for a kind of person, it tells you very little.
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