The strongest claim in What predicts indie success, tested against all of Steam sits in its ladder section: "The single strongest variable in the entire corpus: the best outcome you've achieved so far." The chart behind it reads next-game hit odds off a developer's best game to date: 1.1% if nothing ever cleared 10 reviews, 3.5% past 50, 10.8% past 250, 22.5% past 556, 67% past 5,000. This post re-runs that claim and then tries to break it. It checks whether the number replicates, whether the way it was measured flatters it, whether "best" is really the strongest summary of a career, where the staircase holds and where it bends, and what the rungs are made of.

Two independent copies of Steam went in. F is the post's own data: Fable's July 2026 crawl, 115K games, developers named by their SteamSpy strings. A is Astra's September 2026 crawl, 129K released games, developers named by Steam's own single credits, with current prices, languages and store features. On top of both I used Fable's review histories, the month-by-month review counts of all 34,654 games that had 50+ reviews in July. The histories let me ask a question the post couldn't: how many reviews did a developer's earlier games have on the day the next one launched? Everything below uses the post's conventions unless it says otherwise. That means developers whose first game came out in 2015 or later, next releases through July 2025 (so each has had a year to collect reviews), and a hit defined as 556 reviews.

Short version. The ladder is real. It replicates to the decimal in the post's data, reappears in the independent catalog, and survives every slice I could cut. The post measured earlier games with today's review counts, which includes hindsight. Fixing that makes the middle rungs stronger, not weaker. But "best outcome so far" is not the strongest variable. A developer's typical result (the average of their games on a log scale) predicts the next game better, and so does their most recent game. Once those are known, the best game adds nothing. The reason is that the ladder mostly measures the developer. About two-thirds of the variation in how many reviews a game gets is shared with the same developer's other games, and a peak is a noisy, upward-biased reading of that level. Two more things the ladder hides: most hits still come from people with no ladder at all, and what the next game is (its price and scope, its publisher, whether it goes back to the lane that worked) moves the odds about as much as the rung you start from.

How the check works

A transition is one release by a developer who has shipped before, paired with everything known about their earlier releases. Fable's catalog yields 22,767 of them across 9,283 developers; Astra's yields 32,344 across 12,297. Astra's is larger because Steam's own credits cover developers SteamSpy stopped tracking after 2021. It also drops co-credited games, so the two catalogs define a developer differently, which is useful as a check.

Dating the earlier games. For every earlier game with a review history, I counted its reviews up to the next game's launch day, pro-rating the month the launch fell in. Games with no history had fewer than 50 reviews in July, so their current count is used as an upper bound. To check the method, I compared it against 36 transitions where Astra's session had independently rebuilt each prior game's count from individual review timestamps. My dated counts agree with Astra's on the low/mid/hit band for all 36, with a rank correlation of 0.999, and 94% land within 15% (they run about 6% high, because the histories include a few reviews that don't count toward the store score). One detour is worth recording. My first version rescaled each history to the game's current score-eligible total. That failed on bundle-era games such as Reus and Nihilumbra, where later key-activated reviews inflate the history but not the score, and it halved their early counts. The unscaled version passed and is the one used throughout. The rescaled version gives the same conclusions with slightly larger dated effects.

1. It replicates

Run the post's own code on the post's own data and the ladder comes back exactly: 1.1% / 3.5% / 10.8% / 22.5% / 67.1%. The independent catalog draws the same shape a little lower (17.5% at 556+, 60% at 5K+), mostly because it includes the post-2021 developers SteamSpy misses. The orange line below is the post's chart.

2. The hindsight problem, and why fixing it helps the claim

The post placed each developer on a rung using their earlier games' review counts today. A developer never knows that number when launching. Today's count includes years of long-tail growth, plus any boost the old game got from the new one's success. When the next game hits, players go back to the catalog, the old game's count rises, and the developer gets moved up a rung after the fact. That is the textbook way for a "predictor" to leak the outcome.

The distortion is large. In Fable's catalog, 28% of transitions sit on a different rung once the earlier games are dated, and 30% of the developers the post placed on the 556+ rung hadn't reached it yet when they launched. The leak itself turns out small, though. After a launch, the best earlier game keeps growing whatever happened: median ×1.16 when the next game hit, ×1.36 when it landed mid, ×1.23 when it flopped (Fable's catalog). In Astra's catalog a hit does lift the back catalog more (×1.41 against ×1.15). Most of the movement is ordinary tail growth, and it pushed many developers who were mid at launch into the snapshot's hit rung, where they diluted it. Dating the counts takes them back out. The blue line in the chart is the honest ladder: 5.0% at 50+ (post: 3.5%), 16.2% at 250+ (10.8%), 30.2% at 556+ (22.5%), 47.4% at 1.5K+ (43.1%), 66% at 5K+ (67%). The claim survives its biggest methodological flaw, and the middle rungs are worth roughly 1.3 to 1.8 times what the post said.

A second correction pulls the same way. The post counts every release, so prolific developers with dozens of releases each contribute dozens of rows, and they convert worse at every rung. Count one release per developer (the dashed line) and the 556+ rung reads 37% and the 5K+ rung 81%. Neither weighting is wrong. Per release answers "what fraction of games from this rung hit." Per developer answers "what are the odds for a developer standing on this rung," which is the question the post was asking.

3. Is it the strongest variable? Its family is. "Best" isn't.

To compare variables of different kinds on one scale I used AUC: pick a random release that hit and a random one that didn't, and AUC is the chance the variable ranks the hit higher. 0.5 is a coin flip; 1.0 is perfect. Confidence intervals come from resampling whole developers. The pool is Astra's catalog, because it carries store data: releases #2 onward by steam-era developers, through July 2025, 31,459 releases from 12,106 developers, 7.9% of which hit.

Two readings. First, the post's broad claim stands. The track record family (blue) beats every store-level variable by a wide margin. The best store variable is language count at 0.73, and it is measured today, so successful games that localized after launch flatter it. Primary tag comes in at 0.71, price at 0.66, achievements and controller support around 0.6. Release month, Early Access and having a demo are coin flips. Second, inside the family, "best earlier game" ranks below three other summaries of the same history: the typical result (mean of log reviews) at 0.875, the median at 0.873, the most recent game at 0.859, and only then the best at 0.837. The post's own version (today's counts) scores 0.857, and that edge over the dated best is partly hindsight. The ordering holds at every outcome line from 50 reviews to 5,000 and in both catalogs. Among developers with three or more earlier games, where peak and typical can drift apart, it is 0.880 for the best against 0.896 for the typical.

Those ranking scores understate what this means for an individual developer, because for anyone with a single earlier game the best and the typical are the same number. The clearest test holds the best game fixed and lets the typical result vary. Take developers with at least two earlier games whose best sits on the same rung, 556–5K reviews. The rung alone puts them at about a third. Split them by their typical result:

Same best game, a five- to twelvefold difference in odds. One rung down it repeats: a 50–555 best with a typical under 50 converts at 2.7%, against 12–14% when the typical is in the same range. The reverse doesn't hold. With both in one model, the weight on the best drops from 1.41 to 0.25 while the typical keeps 1.32 (section 4). Averaged over everyone the gain is modest; for the developers whose record holds more than one data point, it is large.

Multivariate models agree (gradient-boosted trees and logistic regression, five folds split by developer so no developer is in both training and test). Best game alone: AUC 0.83. All career variables: 0.89, and dropping the best game from that set changes nothing (0.89). All store variables together: 0.875. Both blocks together: 0.93. So the game itself, read collectively, carries about as much as the whole career does, and the two are complementary. Most of that store signal (language count, tag, price) is plausibly what the developer is able to make rather than a lever, and some of it is measured after the fact.

4. Your latest game matters as much as your best

The fastest way to see the problem with "best" is to hold it fixed and vary the latest game.

A developer whose best game hit but whose latest flopped converts at 13%, about the same as one who never hit but whose latest landed mid-range (13.5%). The same best with a latest hit converts at 55%. In Fable's catalog the corresponding numbers are 15.5%, 15.5% and 57%. In regression terms, the most recent game alone explains more than the best alone (pseudo-R² 0.274 against 0.255), the typical result explains more than either (0.298), and with typical and best in one model the best's coefficient falls from 1.41 to 0.25.

Recency here is counted in games, not years. Among developers whose best dated game is 556+, the next game hits 54% of the time when the best was the previous release, 42% when one release came in between, and 26% when two or more did. By calendar time the decline is gentle: 46% within a year of the best, 36% four or more years later. That fits the post's "time off is free". A long gap barely costs anything; releasing weaker games after the hit does. Two smaller findings point the same way. At equal peak size, a second or third hit adds no consistent lift; the size of the peak matters and the count doesn't. And among mid-rung developers, accumulating more mid games lowers the odds: 10% with one or two, 7% with three to five, 2.7% with six or more.

The odds don't expire after one game; they get re-read. Follow developers forward from their first game that was already 5K+ when the next one launched. The first release after it hits 72% of the time (79% in Fable's catalog), the second 66% (81%), the third 61% (70%). For the same developers tracked across all three, the drift is small: 68%, 55%, 61% (76%, 76%, 70%). What moves the number is the game in between. On the second release after the breakout it's 76% if the first follow-up also hit and 49% if it missed. On the fourth release and later it's 71% against 31%. A 556+ breakout reads the same way one level down: 48% for the next release, 39% and 36% for the two after, and 62% against 13% on the fourth-plus depending on the previous release. The post's 67% for the 5K+ rung was always an average over the next release and the ones after it. The 5K+ samples are small (377 developers in Astra's catalog, 194 in Fable's, under 100 by the third follow-up).

5. Why: the developer is the unit

Here is the fact under the whole ladder. Take every steam-era developer with at least two games and ask how much of the spread in log review counts is shared within a developer's catalog. The answer, as an intraclass correlation:

About 69% of the variation in a game's reach is shared with the same developer's other games. Genre explains 14%, price band 17%, release year 5%. Who made the game outweighs every catalog variable four or five times over. The ladder is what that fact looks like when you read it through one number per developer.

Through that lens, every surprise above stops being surprising. If each game's outcome is the developer's level plus game-to-game noise, the mean of their games is the best estimate of the level. The best of their games is that level plus the luckiest draw, so it runs higher the more games they've shipped and it is noisier. That explains why the number of games shipped turns negative once the best is held fixed. It also explains why the same rung is worth far less late in a career: a 556–5K best converts at 50% on release #2 and at 12% on release #10+. And it explains why content factories with many mid games sit low. I checked this with a simulation that has nothing in it but a fixed level per developer plus noise, using the variances estimated from Astra's catalog: no compounding, no audience, no recency. It reproduces the observed ordering, typical (0.907) over most recent (0.886) over best (0.879), against 0.866 / 0.853 / 0.844 in the real data. The ladder doesn't need anything to compound in order to exist.

That doesn't prove nothing compounds; section 9 finds a modest audience effect. It means the staircase on its own isn't evidence of compounding. Most of it is measurement.

6. The next game usually lands well below the best

A direct consequence of the peak being a lucky draw is that the next game regresses toward the developer's level.

The median next game gets 37% of the best game's reviews at the 50–249 rung and 12% at the 5K+ rung. The chance of beating your best falls as the best rises, from 27% to 11.5%. On a log scale the next game's reviews track the best with a slope of 0.67 (R² 0.24) and the typical result with a slope of 0.82 (R² 0.37). None of this contradicts the ladder: a 5K+ developer's "disappointing" next game still has a median of about 1,300 reviews. It does mean the right expectation after a breakout is your level, not your peak.

7. Where it holds

The coarse version of the dated ladder, cut every way the data allows (Astra's catalog unless marked, releases at least 30 days apart). Each row is one slice; the cells are the odds the next release reaches 556 reviews from that rung, "–" means fewer than 25 releases, and the last column divides the 556–5K rung's odds by the 10–49 rung's.

The staircase survives everything. It holds in every era, every price band, self-published or not, sequel or new IP, same genre or pivot, short gap or long, second release or tenth, small catalog or factory, and at every outcome line from 50 to 5,000 reviews. In no slice of developers is the 556–5K rung less than five times the 10–49 rung (only the easy 50-review outcome line compresses it, to 4×). That is a robust descriptive fact about Steam, and the post was right to lead with it.

8. Where it bends

Price and scope flatten it. Among cheap next games (under $5) the 556–5K rung converts about 22 times as often as the 10–49 rung. Among $20+ games it's 5 times, because the floor rises. A developer with no traction whose next game is $20+ hits 8–12% of the time, which is about what a sub-$10 game gets from the 250–555 rung. Part of what the ladder measures is project size: higher-rung developers make bigger games next. The median next price climbs from $4.99 at the bottom rungs to $17.99 at 5K+, and the share priced $15 or more from 7% to 51%.

Publishers raise the floor. When someone else publishes the next game, the bottom rung converts at 3.4% instead of 0.8%, and the 50–249 rung at 12% instead of 5%. A publisher works like a borrowed rung, with the usual caveat that publishers pick projects that already look promising.

Late-career rungs are worth less. The same 556–5K best converts at 50% on release #2, 36% on #3–4, 30% on #5–9 and 12% on #10+. Developers with 21+ games in total convert at 16% from that rung. "Best so far" doesn't know how many tries it took; the typical result does.

The top rung is a studio rung. The 5K+ rung holds 712 releases from 376 developers in Astra's catalog: Rockstar, Respawn, Blizzard, Maxis, NetEase and Behaviour alongside Toby Fox, Landfall and Motion Twin. Its 60–66% isn't an indie number. It also contains the classic failure: Behaviour followed Dead by Daylight with What the Fog (264 reviews), and Maxis followed The Sims 4 with a MySims re-release.

The era decline depends on the yardstick. On cumulative reviews the ladder looks weaker since 2021. Calibrate it on 2016–20 launches and it over-predicts 2021–25 hits by about 30% (it predicted 2,175, and 1,551 happened), though it still ranks them almost as well (AUC 0.84). But older games have had longer to collect reviews. Measure each next game by its first year instead and the 2016–20 ladder predicts 2021–25 almost exactly (1,429 predicted, 1,484 actual). Measure it as "top 5% of that year's releases" and the 556–5K rung is worth more now than in 2016–18 (19–23% against 14–16%). The shape and the ranking are stable. The levels move with whatever ruler you hold up.

9. What the rung is made of

Reach, much more than approval. If higher-rung developers made better-liked games, the next game's positivity would climb with the rung. It barely does: the median goes from 80% to 84%. Among next games that hit, it is flat across rungs (85–88%), so a hit from a newcomer is as well-liked as one from a veteran. What climbs is the count: the median next game with 50+ reviews has 117 reviews at the bottom rung and 1,741 at the top.

Some audience shows up at launch. Holding the next game's size fixed (556–1,500 first-year reviews), the first 30 days bring 35–40% of the first year's reviews when the developer sits on the bottom three rungs, and 43–44% from the 250+ rungs. Established developers launch into people who were waiting for them. This is the one place the compounding story shows up directly, and it is modest.

Going back to the lane that worked amplifies it, in both directions.

After a 556–5K best, a next game in the best game's primary tag hits 45% of the time, against 31% for a change of tag. At 5K+ the split is 85% against 58%; for the same title family it is 52% against 31%. At the bottom it flips: from the 10–49 rung, keeping the tag hits less often (1.3% against 3.3%), and after any sub-50 best it reaches 50 reviews less often (13% against 17%). That is the post's "pivot after a miss," and here is its mirror: return after a hit. This seems to contradict Astra's earlier check, which found genre-staying worth nothing after a hit (43.6% against 42.8%), but the two compare different things. Astra compared the next game with the previous release. Run that comparison here and it comes out null too (42% against 40%, one release per developer). Compared with the hit's lane, it holds with one release per developer (55% against 40%), and holds with controls for rung, typical result, latest result, price, publisher and gap (odds about 2.2× in both catalogs). What matters is going back to the lane that worked, which is often not the latest one.

Scale and partners. Higher rungs make pricier games and more often have a publisher (17% at the bottom, 37% at the top). In a model of the high-rung developers, a higher next price and an outside publisher each carry independent weight.

10. Most hits come from nowhere

The ladder describes odds. In headcount, most hits still come from developers with no ladder at all.

First games supply 61% of all hits in the window, falling from 75% in 2016–17 to 52% in 2024–25, while developers who already had a 556+ game went from 10% of hits to 30% (part of that rise is mechanical, since 2015 starters needed time to land a first hit). Releases after only sub-50 games have the lowest odds anywhere (1–3%) but still supply 5% of hits. Low odds times a huge population is still a lot of hits. The ladder tells you whose next game to bet on; it doesn't tell a newcomer the door is closed.

11. How the ladder fails at the top, and how people climb from the bottom

Contrast the extremes. On the 556+ rung, compare next games that hit with next games that fell under 50 reviews. On the bottom rungs (best under 50), compare the rare escapes with the usual outcome.

The flops at the top are mostly side projects: cheap, quick, self-published, off-lane, often from developers on their sixth release or later. The escapes from the bottom are mostly scale-ups into a new lane: about three times the price, twice as often with a publisher, a longer gap, and away from the genre that failed. In both cases what the developer does next pushes the rung's odds around, which is why the ladder alone stops at AUC 0.84 to 0.87.

12. A worked example: one career through all of this

The post used this site's own games as a case, so here is one career read through every finding above. Treat it as a use case for the concepts, not a forecast: every cohort below is a few hundred developers or fewer, and the cohorts include studios. On Steam the career is two games. BYTEPATH has about 306 reviews (about 237 when SNKRX launched, by this method; Astra's per-review reconstruction gives 219), and SNKRX has about 4,200. That is one hit near the top of the 1.5K–5K rung, one mid-range game, and the hit is the latest release. With two games the typical result is about 1,100 reviews, which already places this career in the "hits are the norm" row of section 3.

Is a prior hit the strongest thing in the record? Descriptively, yes. No store variable comes close, and the dated ladder makes the jump steeper than the post did:

Two qualifications come from the rest of this post. "Any" hit overstates it. A hit that is an outlier in a failing catalog converts at 4.5–12% (section 3), no better than a steady mid-range developer who never hit, and a hit followed by a flop converts at 13% (section 4). "Predicts" is not "causes". About 69% of a game's reach is shared with its developer's catalog, and a model with nothing in it but a fixed level per developer plus luck reproduces the ladder (section 5), so most of the rung is the developer showing through. What the data credits to the hit itself is smaller: an audience that shows up at launch, and roughly double the odds when the next game goes back to the hit's lane (section 9).

What does the next release look like for this profile?

About 50–60%, with a 95% range of roughly 42–72% on the 58%. For the base profile, about 44% of next releases reach 556, 30% reach 1,000, 6–16% reach SNKRX's size (4,000+), 43–47% land at 50–555 and 10–13% fall under 50. The median next game gets about 400 reviews, or about 800 when the hit is the latest release.

What should the next game be? Among developers whose best is 1.5K–5K (any record, so the cells are larger):

The best cell is the hit's lane at a higher price, and a new title in the same genre does about as well as a sequel. SNKRX's primary tag is Action Roguelike, so for this career the lane is action roguelikes, not SNKRX 2 specifically. Two readings keep this honest. Price stands for scope here (it is today's price, and SNKRX itself sold at $2.99), so "$10+" means a bigger game, not a bigger number on the same game. And the cells include studios with budgets and publishers, who may already hold a strong project when they choose a bigger same-genre follow-up. It is the best-odds cell, not a lever.

What if mid-range games come first? Follow developers from their first hit through any later releases that all land at 200–555 reviews (their final counts), and ask what the next release does. Few developers ship two or more such games after a hit, so the last column uses a looser 50–555 band to get cases:

Each mid-range result roughly halves the odds: about 50%, then 25%, 15%, 10%. By the third, the developer sits about where a mid-range developer who never hit sits (around 12%). A game at 200–500 reviews is not a failure, but the record reads it as evidence about the developer's level all the same, and the one hit counts for less with each new data point. Part of the drop is selection (developers who keep shipping small games after a hit are mostly small, prolific ones), and the data can't tell whether a small release hurts the next one or only reveals something. In the profile above, a mid-range game after the hit took the following release from 58% to 38%; a flop after a hit takes it to 13%.

How does that square with "a hit means about a 50% chance"? The rung averages pool everyone standing on a rung at any point after their hit. Among developers whose best dated game is 556+, the next release hits 54% when the hit was the previous release (1,408 cases), 42% with one release since (658) and 26% with two or more since (1,396), about 40% pooled. The releases in between can be anything: further hits keep the odds near 70%, mid-range results walk them down the table above. A hit is worth about 50–60% right after it, and it stays there only while later results keep landing. The odds don't fade with time (a four-year gap barely matters); they fade with evidence.

For this career, then: the record says roughly 50–60% for a real follow-up, the best version of that follow-up in the data is a bigger game in the hit's lane, and the thing to plan around is that small releases landing at a few hundred reviews would read as a lower level before the next real one comes out. Updating SNKRX doesn't count as a release in any of this.

The revised claim

The post's sentence should change. A version the data supports:

Your track record is the strongest predictor of your next game. Read it as your typical result and your latest result, not your best. Your peak is the most flattering summary and the weakest one. It is a lucky draw from your level, inflated further when measured with today's review counts, and it is worth less the more games it took to get there. The record mostly measures you: about two-thirds of the variation in a game's reach is shared across its developer's catalog. That's why the staircase is so robust, and also why it isn't by itself evidence that anything compounds. Something does compound, modestly: established developers launch into a waiting audience, and going back to the lane that produced the hit roughly doubles the odds of hitting again. The rest of the variation is the game. Price and scope, a publisher, and whether it returns to the lane that worked move the odds about as much as the rung does.

What stands from the post, after all of this: every rung multiplies the next game's odds, the staircase is smooth with no magic threshold, pivoting after a miss beats doubling down, and time off costs little. What changes: the honest middle rungs are higher than the post's numbers; your latest game counts as much as your best; a hit's weight fades with each non-hit release after it, not with time; and after a hit, the risk to plan around is the cheap, quick, off-lane follow-up.

Limits

• Reviews stand in for sales. The 556-review line only means "25,000 copies" under the post's calibration from two games.
• Developer names aren't people. Teams split, merge and rename; Fable's catalog uses SteamSpy strings and Astra's drops co-credited games. Both catalogs agree, which helps, but neither identifies individuals.
• Store data (price, languages, features, tags) is today's, not launch day's. Language count in particular is partly a consequence of success.
• Delisted games are invisible in both catalogs.
• The review histories exist only for games that had 50+ reviews in July 2026. Below that, earlier games keep their current counts, which can slightly overstate the bottom rungs' history.
• Everything here describes what happened. None of it is a controlled experiment, and the cohort rates in section 12 aren't calibrated personal forecasts.

Every number here comes from the primary data: both Steam catalogs, Fable's 34,654 review histories, and nothing else. The claims being checked are from What predicts indie success, tested against all of Steam, which was built from the same research corpus.