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Mobile Gaming’s Survival is Married to the U.S. Economy; It Should Ask for A Divorce

If you’re European, you need the U.S. economy to grow. If you’re Canadian, you need the U.S. economy to grow. This sobering reality underscores nearly every Western mobile development hub today: for mobile gaming to grow, the U.S. needs to grow. Although optimistic narratives from developing markets like India and Brazil are abundant, their growth rates still pale compared to the U.S.’s real spending power growth. For the foreseeable future, it’s U.S. or bust in mobile gaming, a reality suggesting mobile gaming doesn’t control its destiny.

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Digest or Die: Tripledot’s Big Gamble

Tripledot’s nearly $1B acquisition of Applovin’s studio collection appears to be a massive and leveraged gamble but reflects the shrinking pool of the hyper-to-hybrid publisher game of musical chairs. With the stroke of a pen, Tripledot’s revenue portfolio radically shifts from 1% IAP to being a majority. Meanwhile, Voodoo, Homa, and others undergo painful and slow transitions in hybrid-style games, with success stories like All In Hole taking over two years to release after Attack Hole’s 2022 release. Rather than incremental growth, Tripledot bet on transformative integration in one dramatic move. While there’s massive operational risk, if Tripledot can digest Applovin’s studio collection, the product will be larger than the sum of its new parts.

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The Economics of Match Events

Nearly all economic activity in match-based or “saga”-based metas follows the fundamental relationship:

[ text{Revenue}_{i} = text{Gold Sink}_{i} = text{Attempts}_{i} cdot text{Gold Sink Per Attempt}_{i} ]

where,

(bullet) (text{Revenue}_{i}) is the revenue for the (i)th player. (\) (\) (bullet) (text{Attempts}_{i}) is the number of attempts made by the (i)th player. (\) (bullet) (text{Gold Sink Per Attempt}_{i}) is the average of gold spent per attempt by the (i)th player. (\)
(\) Holding (text{Gold Sink Per Attempt}) constant, an increase in (text{Attempts}) leads to higher (text{Revenue}). Similarly, increasing the (text{Gold Sink Per Attempt}) while holding (text{Attempts}) constant also raises (text{Revenue}). Many innovations in match economies operate within this framework. For instance, a “super light ball” mechanic increases (text{Attempts}) but reduces the (text{Gold Sink Per Attempt}). Events follow the same structure.

Basic Match Model

At the aggregate level, revenue across all players is: $$ text{Revenue} = sum_{i}bigl(text{Attempts}_{i} cdot text{Gold Sink Per Attempt}_{i}bigr) $$
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Fisharian Game Economy Tradition
Ever tried Dr.Mario stimulus?

Game economy designers have inadvertently revived the economic traditions of famed economist Irving Fisher. In Fisher’s world, the economy is a hydraulic machine, with refinement or “productive process” occurring as resources flow. The impact of major institutions takes on a literal effect, where a tariff might slow the flow of liquid or capital from one chamber or country to another. It’s a surreal approach and the early attempt at modeling game economies.

Irving Fisher studied monetary theory and price levels at Yale, where his obsession with equilibrium led to an extraordinary invention. In 1891, he unveiled his hydraulic-mechanical computer—a contraption of water, pulleys, and floats that physically demonstrated how prices find their level. The machine, described in his paper “Mathematical Investigations in the Theory of Value and Prices,” became the first working economic model, translating abstract theory into observable mechanics. It was part of a broader effort to formalize economic theory—something game economy design desperately needs.

Tools like Machination and Excel carry Fisher’s torch, albeit in digital form. Machination’s node-based diagrams mirror Fisher’s hydraulic logic: resources pool, flow, and transform through gates and converters. The Excel models do the same, but the piping and transformation process is more opaque (another reason it fails as a tool).

The economy designer is a new role that’s emerged only in the wake of live services played over the course of years. Live services, or long-time horizons, make virtual currency viable for lowering transaction costs (hundreds of IAP transactions mean credit card fees and awkward UX) and crafting complex time/money supply chains. This highlights currencies’ key roles as stores of value and units of accounting.

The economic model becomes necessary to understand these time and money supply chains, much as Fisher’s hydraulic computer was necessary to understand price equilibrium. If the only way to understand a supply chain is to solve something down it, then the economy model’s goal is to do just that. The result is an ability to understand unintended consequences between overlapping progression institutions and design the shape of key game KPIs.

The irony of modern game economies lies in their reliance on century-old methodologies. While Fisher’s hydraulic principles find new relevance in persistent digital economies, our tools remain trapped in the past. The field desperately needs reproducible, accessible modeling systems that simplify—rather than replicate—the complexity of modern virtual economies. Reproducibility and accessibility remain elusive, continuing to be the Achilles’ heel of game economy design.

AI In Gaming Has Flopped

Humanity may be on a colossal technology frontier, but gaming is being dragged along with AI. Instead of surfing atop the wave, it’s retreated to the wake. Gaming has historically been the first-best use case for new technology, so where did it all go so wrong?

In the 26 months since ChatGPT launched, Web3 has made more tangible progress than AI gaming applications. Any technology outpaced by Web3’s progress is in danger of irrelevance. And it’s for good reason: so far, AI’s visible footprint in games has been limited to a series of Cosmic Lounge press releases (I want my match-3 levels!) and a sixth finger in Call of Duty key art. Everything else appears to be cheap VC slideware or corporate investor day fantasies.

It’s true that gaming effectively subsidized the AI revolution by bankrolling Nvidia’s GPU development, ultimately creating a problem set whose solution unlocked accelerated AI growth. However, it’s failed to capture the subsequent gains, as code development is on a tear; real-time voice translations are consumer-grade, and medical diagnosing is advancing. Gaming has pioneered advancements in real-time 3D graphics, physics simulation, haptic feedback, and internet infrastructure expansion via demand acceleration and has taken wrong turns, too. Cloud gaming, motion controls, plastic guitars, and subscriptions don’t look like they work. Web3 looks like it will register as our next wrong turn, not because it’ll die, but because it’ll fail to grow.

When Do You Write Off the Forte Money?

On the demand side, most game applications are demos, while conversing with NPCs—the most rudimentary possible use case—is lauded as a compelling feature. For an industry that prides itself on the fusion of art and science, we must reclaim our heritage of pushing technological boundaries rather than simply implementing API wrappers.

On the supply side, the pursuit of optimized match-3 gameplay illustrates our current limitations. While we understand that level design significantly impacts retention, determining optimal sequencing amid countless variables remains a formidable challenge. AI promises to accelerate the supply chain, but the bottleneck has shifted downstream to fundamental design questions.

Web3 represents a fascinating detour that consumed substantial venture capital, yielding little except the employment of millions of Southeast Asian players who beat local wages through trading virtual value (true!). Whether the answer lies in Roblox text prompts or voice-command FPS demos remains unclear, but there is still room for a team to experiment. Gaming needs to return to Hoffman’s philosophy: “If you’re not embarrassed by your first release, you shipped too late,” and try getting embarrassed ASAP.

The Game is Outside the Game

Matthew Ball’s 2024 gaming review paints an industry that had a good ride but is settling into stagflation. The Metaverse is nowhere to be found; instead, growth drivers like cloud streaming and GTA pricing replace it. If Stadia is the best we can do, we’re truly fucked. I wrote in agreement earlier this year with “Gaming’s Best Years Are Behind It.” I stand by the same pessimism, but there’s an essential factor that may well guarantee gaming’s growth: time.

Over the past decade, gaming’s largest achievement has been its pliability: it can adapt to any format—smart TV, smartwatch, smartphone, and increasingly health and financial apps. It’s not just a form factor; the business models bend too. F2P didn’t just take share from traditional box revenue; it expanded the audience of gamers. Now even Grandma plays Candy Crush. Without real momentum behind a new control factor (AR/XR), and with smartphone, console, and PC growth limits reached, the audience appears maximized. Surely, revenue will follow at some point.

The metrics demonstrated by early “gaming cohorts” suggest realtized growth that’s yet to revibrate among the DAU base. If we consider gaming itself a product, we observe that new cohorts are far more engaged age-over-age than in earlier generations. As a reminder, Roblox maintains 380 MAU, with about half the kids in the United States as active users. Roblox’s users are aging, and even if they churn from the platform, the more important question is whether they retain gaming as a whole, with spending power growing alongside income.

As the current Roblox generation ages and habits are maintained, new, more engaged cohorts will stack, changing the relative share of gaming engagement. Of course, monetization must follow as Roblox struggles to grow user spend. So far, they haven’t released monetization metrics as cohorts age.

The best source for time trends comes from the American Time Use Survey, which gives diaries to Americans and has coders classify entries. Among 15-24 year-olds, minutes played per day is over two hours, up from 1hr 40min in 2023. This minimizes the Roblox effect, as those cohorts just reach maturity enough to be counted 15 and above in the survey.

Not every cohort is up, however. Despite clear jumps in engagement, the new millennials (25-34) are not trending upward. In 2003, these cohorts would have been born in 1978 (Space Invaders), while the most recent age participants would have been born in 1998 (considered the greatest year in gaming of all time). It makes sense, then, that the 25-34 year-olds are poised next to see these most engaged cohorts enter the pool.

Meanwhile, the rest of the age groups are holding onto COVID highs but show no obvious long-term growth.

It’s important to remember that the coders for the time use survey have to follow strict rules on categorizing entries. The specific games category includes the computer, so it’s unclear if mobile games would fall in the same code:

  1. Playing games on the computer (including Internet games): Code as
    Socializing, Relaxing, and Leisure/Relaxing and Leisure/Playing games
    (120307).

Still, it’s puzzling how stable the trends are for the rest of the age cohorts. Are 75 year olds really playing an hour of games per day?

At least multiple reports have picked up on the rise in young men’s gaming habits, enough to cause controversy as a scapegoat for lower labor force participation. This has doubles down on a shift in gaming comprising a larger share of total leisure time. In other words, as consumers exhibit more leasure time, we find that they spend it increasingly on gaming.

The holy grail is more longitudinal data of consumer preferences over time. Fortnite is celebrated as a graduation game from Roblox, but it’s unclear if that’s reality or if engagement instead withers away in place of other obligations. For gaming to remain relevant, it needs to continue to bend across age groups, with the NY Times Wordle as relevant as Star Stable in monetizing over the lifetime of a customer.

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