How Much Will Your Game Earn From Ads? A Mobile Game Ad Revenue Calculator, 2026 Inputs, and Three Worked Examples

Mobile game advertising is no longer side income for a handful of genres. According to Sensor Tower's ad monetization report published in 2026, mobile game ad revenue topped $12 billion in 2025 across just the 19 countries the firm estimates, on 2.4 trillion ad impressions. The share of games that monetize with ads rose from 45.1% in July 2021 to 55.6% in May 2026. More than half of all games now run ad monetization.

Yet the question "how much can our game earn from ads?" is surprisingly hard to answer. It comes up when talking to a publisher, when weighing a hybrid conversion, and when setting a ceiling on UA spend, and most online ad revenue calculators ask for just two numbers: DAU and eCPM. Actual revenue is decided by what sits between them: ad opportunities, engagement, fill rate, and retention.

eCPM values themselves are covered in What Are 1,000 Ad Impressions Worth? 2026 Mobile Game eCPM Benchmarks by Format, Region, and OS, and the Q4 Price Window, and reading revenue as DAU times ARPDAU is covered in Revenue = DAU × ARPDAU: The Daily Metric That Separates Real Growth From Install Spikes. This post ties those pieces into one calculation. It sets out the inputs that can be verified as of October 2026 and where they come from, a calculator table you can reuse as is, three worked examples by genre, how to convert the result into ad LTV, and the most common reasons forecasts miss.

How Do You Calculate a Mobile Game's Ad Revenue?

A mobile game's daily ad revenue is the sum, across ad formats, of DAU × ad opportunities per DAU × realized fill rate × eCPM ÷ 1,000. Divide daily revenue by DAU and you have ad ARPDAU; multiply that by the area under the retention curve, which is the expected number of active days per player, and you have ad LTV.

The familiar "impressions × eCPM ÷ 1,000" is not wrong, but it leaves out how you predict impressions. Impressions only become forecastable once you break them into three parts. The first is the ad opportunities your game design creates. For interstitials that is sessions per day × ad slots per session; for rewarded ads it is the share of players who choose to watch × how many times those players watch per day. The second is the share of those opportunities that actually got filled and displayed. Google AdMob splits this into two steps: match rate is the percentage of ad requests that received a response from an ad source, and show rate is the percentage of returned ads that were actually displayed. This post calls the product of the two the realized fill rate. The third is eCPM.

The table below is the calculator. Work out one row per format and add them up.

Two cautions. eCPM is revenue per 1,000 impressions, so never multiply it by requests; if you want a request-based view, calculate revenue per 1,000 requests separately. And offerwalls do not belong in this table. An offerwall's eCPM uses offerwall screen opens rather than ad impressions as its denominator, so putting it on the same line overstates it; model it as its own line, participating users × revenue per participant. The reasoning and figures are in How Much Do Offerwalls Really Lift Retention and Revenue? 2026 Benchmarks and the Conditions That Cannibalize IAP.

Where Do the Calculator Inputs Come From?

eCPM and retention have public benchmarks, but impressions per DAU and rewarded engagement rate have no reliable neutral benchmark. Use external figures only to set ranges, and take the impression inputs from your own game's logs.

Industry sources acknowledge this. In its 2026 comparison of F2P monetization models, Game Growth Advisor states that both inputs to ad ARPDAU, impressions per DAU and eCPM, have to be measured by the studio, that no published benchmark exists for impressions per DAU, and that the often-quoted "3 to 5 per day" is a design recommendation rather than a measurement. The same goes for rewarded engagement: many of the figures that turn up in search come from ad networks reporting on their own data or from surveys several years old.

What does exist is structural data you can use to estimate ad opportunities.

The TopOn figures are useful because they show the gap between share of impressions and share of revenue. In casual games, banners deliver 37% of impressions but only 6.5% of revenue, while rewarded video turns 21% of impressions into 39% of revenue. That is why adding banner impressions in a calculator barely moves the total.

The roughly $5 per 1,000 impressions derived from Sensor Tower is a blend of every format and country, so it cannot serve as a target, but it works as a sanity check. If your model's blended rate (total ad revenue ÷ total impressions × 1,000) is several times higher or lower, check whether the format mix explains it or whether your assumptions are stretched.

Worked Examples: Hyper-Casual, Hybrid-Casual, and Rewarded-Only Midcore

At the same 100,000 DAU, daily ad revenue can land in a similar $2,000–$3,000 band across very different ad setups, but the way that revenue is produced differs completely. The inputs in the three examples below are assumptions chosen within the ranges above, not measurements from any specific game.

eCPMs were picked within the global ranges summarized in the eCPM benchmarks post (Playwire, 2025: rewarded $8–$18, interstitial $2.5–$5, banner $0.2–$0.8), and the midcore rewarded eCPM was set at $15 on the assumption of a heavier tier 1 mix. Interstitial slots per session were kept well below the 4–6 per session ceiling AdReact describes.

Example A: Hyper-casual (interstitial + rewarded + banner, assumptions)

At 100,000 DAU that is about $3,410 a day, or about $102,000 over 30 days. An ad ARPDAU of $0.034 falls at the low end of the $0.03–$0.08 hyper-casual ARPDAU range Game Growth Advisor gives. Because 63% of revenue comes from interstitials, this game's revenue is most sensitive to its frequency cap.

Example B: Hybrid-casual (rewarded-led with light interstitials, assumptions)

Ad ARPDAU is $0.031, almost identical to the hyper-casual example, or about $3,130 a day at 100,000 DAU. Hybrid-casual adds in-app purchase revenue on top of this. The genre's revenue mix and how ads and purchases interact are covered in Hybrid-Casual Monetization: The Economics Behind the Genre Everyone Is Converting To.

Example C: Rewarded-only midcore (assumptions)

With no interstitials or banners, ad ARPDAU is still $0.029, about $2,850 a day at 100,000 DAU. A rewarded-only setup sells fewer impressions at a higher price, and the absence of forced exposure that erodes retention is what makes the difference in ad LTV in the next section.

Compute each example's blended rate and hyper-casual comes to about $1.6 per 1,000 impressions (because of the banner volume), hybrid-casual about $8.5, and midcore $15, the rewarded rate itself, spread on both sides of Sensor Tower's $5 average. Similar daily revenue can come from selling many cheap impressions or a few expensive ones.

What Changes When You Turn Ad ARPDAU Into Ad LTV?

Ad LTV is ad ARPDAU multiplied by a player's expected active days, and even games with similar daily ad revenue per user end up nearly three times apart on D90 ad LTV because of retention.

Expected active days is the sum of daily retention with install day (D0) counted as 1, in other words the area under the retention curve. The retention assumptions are as follows. Hyper-casual has no published genre-level figures, so the example uses the top-quartile level from GameAnalytics' 2026 benchmarks (D1 just above 30%, D7 6–7%, D30 1.6–1.8%). Hybrid-casual uses the D7 of about 20% and D30 of about 10% cited by Game Growth Advisor, with an assumed D1 of 40%. Midcore assumes D1 40%, D7 15%, and D30 6%. D90 values and the days in between are assumptions and interpolations.

Hyper-casual had the highest daily rate, yet hybrid-casual's D90 ad LTV is 2.8 times higher. In an ad revenue forecast, thickening the retention curve is a bigger lever than adding a dollar of eCPM.

These results need to be checked against real market averages. In AppsFlyer's 2026 report, which analyzed $7.2 billion of in-app ad revenue from January 2025 to March 2026, D90 in-app ad ARPU (global averages) was $0.55 for casual, $0.47 for casino, $0.40 for midcore, and $0.22 for hyper-casual. All three examples land below those figures, because their eCPMs were set at global ranges; AppsFlyer also notes that North America and Europe run higher than average. If your own model comes out several times above these averages, your inputs are probably optimistic; if it comes out several times below, check whether you have applied eCPMs from cheaper countries than your traffic actually comes from.

The same report shows that ad revenue is front-loaded. Across all apps, about 57% of D60 in-app ad revenue arrived by D1 and 89% by D7, and for hyper-casual 63% arrived by D1. Ad LTV is largely settled in the first week, which makes first-week retention the central variable in ad monetization. How to turn ad LTV into a CPI ceiling is covered in the ARPDAU post.

What Should You Account For When Turning Daily Revenue Into a Monthly Forecast?

The core of a monthly ad revenue forecast is treating DAU not as a fixed input but as the result of new installs and retention, then layering eCPM seasonality on top.

Steady-state DAU is roughly daily new installs × expected active days. If the hybrid-casual game in Example B brings in 10,000 installs a day, multiplying by 9.5 expected active days through D90 holds DAU at around 95,000. Stop UA and DAU decays along the retention curve. A monthly forecast built as "100,000 DAU × 30 days" quietly assumes that UA spend continues at today's level.

Seasonality enters through eCPM. As summarized in the eCPM post, AdReact puts Q4 eCPMs typically 20% to 40% above Q1, and Felix Braberg, who writes a newsletter on mobile ad revenue, gave the example of a US iOS rewarded placement falling from $18 in December to $11–$12.50 by mid-January. The same post shows that the rise is not even across placements and countries.

The percentages in the table are applied uniformly to every placement for simplicity; in practice they should be applied by country and format. Even so, the table makes clear that the same game at the same DAU can swing from the low $60,000s to over $100,000 a month on seasonality and fill rate alone.

What Are the Most Common Ad Revenue Forecasting Mistakes?

Most ad revenue forecasts miss because of what sits outside the calculator. Assuming 100% fill, ignoring seasonality, holding DAU fixed, and leaving out IAP cannibalization are the most common.

The first mistake is skipping fill rate. Multiply ad opportunities straight by eCPM and unmatched requests and undisplayed ads get counted as revenue. Raising a price floor lifts eCPM but lowers fill, so judge by revenue per 1,000 requests or ad ARPDAU rather than eCPM. This mechanism is covered in the section on what moves eCPM in the eCPM benchmarks post.

The second is ignoring seasonality. Build an annual forecast from October to December data and January will open a large gap. Compare against the same month last year, not the previous quarter.

The third is ignoring retention decay. Multiply launch-period DAU by ARPDAU to get an annual number and you leave out the way the retention curve erodes DAU. Calculate with retention area by cohort.

The fourth is judging a frequency increase after three days. More impressions lift revenue the same day, but the retention loss appears between D3 and D7. An honest model shrinks retention area the moment it adds ad opportunities. What a single interstitial costs in retention is covered in The Real Price of an Interstitial: What One Full-Screen Ad Costs You in Retention.

The fifth is leaving out IAP cannibalization. When rewarded ad or offerwall rewards substitute for paid items, purchase revenue falls by part of what ad revenue gains. The forecast should carry net incremental revenue, ad revenue gained minus purchase revenue cannibalized, and that number can only be found by comparing against a holdout group that does not see the ads. In AppsFlyer's report, the ad share of revenue in games running all three models fell from 63% in January 2025 to 56% in early 2026; the split between ads and purchases is not a constant. The principles for balancing the two are in Balancing IAP and Rewarded Ads Monetization: How Two Revenue Models Work Together.

The sixth is applying one blended eCPM to every country. Scale UA in low-price countries and the average eCPM falls even though nothing about the game got worse. Enter eCPM and retention by country and OS and add them up at the end.

Retention Is the Biggest Lever in Ad LTV: The Playio Perspective

In the worked examples, the game with the highest daily ad rate did not win on D90 ad LTV; the game with the most expected active days did. The more a game relies on ad revenue, the more a UA team is buying not an install but the number of days that player will stay.

Playio works on that number of days. It runs an Android-based gamer community of five million players, analyzing genre preferences, play history, and in-game behavior data to connect games with players whose tastes match, and it uses playtime-based rewards to turn repeat logins in the first week after install into a habit. Given that 89% of D60 ad revenue arrives in the first week, more active days in that first week translate directly into higher ad LTV. Pricing is CPI by default, and CPE based on reaching a playtime threshold or completing a specific in-game action is also supported, so the ad LTV from the calculator can set the ceiling on what you pay per install or per action.

You can find more details here. (https://playioadsen.oopy.io/bizdeck)

Key Takeaways

As of October 2026, a mobile game's daily ad revenue is the sum across formats of DAU × ad opportunities × realized fill rate × eCPM ÷ 1,000, converted into ad LTV by multiplying by the area under the retention curve. eCPM and retention have public benchmarks, but impressions per DAU and rewarded engagement rate have no neutral benchmark, so those two inputs have to come from your own logs. In three examples built on stated assumptions, ad ARPDAU was similar at around $0.03, yet D90 ad LTV spread from $0.11 to $0.30, nearly threefold, because of retention. Check the results against AppsFlyer's D90 in-app ad ARPU ($0.55 for casual, $0.22 for hyper-casual, and so on) and Sensor Tower's blended average of about $5 per 1,000 impressions, and build monthly forecasts that account for DAU driven by new installs, Q4 and January seasonality, fill rate, and IAP cannibalization. In the end, ad revenue is decided less by how many impressions you sell than by how many days players stay.

For inquiries about Playio's advertising solutions, reach out at: [email protected]

Sources

• Sensor Tower ad monetization report, summarized by Game World Observer, July 2026 (2025 mobile game ad revenue above $12B across 19 countries; 2.4T ad impressions; share of games with ad monetization 45.1% in July 2021 to 55.6% in May 2026): https://gameworldobserver.com/2026/07/06/in-2025-mobile-game-advertising-revenue-exceeded-12-billion-analytics

• Deconstructor of Fun, 5 Numbers Hiding in Plain Sight: Sensor Tower's Ad Monetization Report, August 2026 ($12B is a floor covering 19 countries; 2.4T impressions): https://www.deconstructoroffun.com/blog/5-numbers-hiding-in-plain-sight-sensor-towers-ad-monetization-report

• AppsFlyer, The State of App Monetization 2026 ($7.2B in-app ad revenue, January 2025 to March 2026; D90 IAA ARPU casual $0.55, casino $0.47, midcore $0.40, hyper-casual $0.22; 57% of D60 ad revenue by D1 and 89% by D7, hyper-casual 63% by D1; ad share in three-model games 63% to 56%): https://www.appsflyer.com/resources/reports/app-marketing-monetization-report/ (summary: https://gamedevreports.substack.com/p/appsflyer-app-monetization-in-2026)

• Game Growth Advisor, F2P Monetization Models 2026, April 2, 2026, updated September 1, 2026 (ad ARPDAU inputs must be measured; no published benchmark for impressions per DAU; "3-5 per day" is a design recommendation; hyper-casual ARPDAU $0.03-$0.08; TopOn H1 2025 format shares of revenue and impressions): https://gamegrowthadvisor.com/blog/2026-04-02-f2p-monetization-models-comparison-2026/

• Game Growth Advisor, Hybrid Casual Games 2026, April 16, 2026, updated August 1, 2026 (hybrid-casual D7 around 20%, D30 around 10%, citing Matej Lancaric): https://gamegrowthadvisor.com/blog/2026-04-16-hybrid-casual-game-design-strategy-2026/

• GameAnalytics, 2026 Mobile & PC Gaming Benchmarks (16,000+ mobile games, 2025; sessions per day median 3.8-3.9, top quartile 5.3-5.7; session length median 3.1-3.5 minutes; top-quartile retention D1 just above 30%, D7 6-7%, D30 1.6-1.8%): https://www.gameanalytics.com/reports/2026-mobile-pc-gaming-benchmarks

• Google AdMob Help, Reports glossary (definitions of match rate, show rate, requests, impressions, eCPM): https://support.google.com/admob/table/9462111?hl=en

• AdReact, Interstitial Ad Best Practices for Mobile Games, May 8, 2026 (4-6 per session ceiling, 2-3 minutes between ads, Q4 eCPM 20-40% above Q1): https://adreact.com/blog/interstitial-ad-best-practices-mobile-games/

• Felix Braberg, Your eCPMs Didn't Break; They Went on Holiday, August 26, 2026 (US iOS rewarded $18 in December to $11-$12.50 by mid-January; practitioner observation): https://felixbraberg.substack.com/p/your-ecpms-didnt-break-they-went

• Playwire, AdMob eCPM Benchmarks: What Publishers Should Expect, September 17, 2025 (global ranges: rewarded $8-$18, interstitial $2.5-$5, banner $0.2-$0.8): https://www.playwire.com/blog/admob-ecpm-benchmarks-what-publishers-should-expect

• Worked examples A, B, and C (ad opportunities, engagement, fill rate, eCPM, D1 and D90 retention, scenario percentages): illustrative assumptions and our own calculations; retention curves use power-law interpolation between D1, D7, D30, and D90, summed from D0 to Dn