Risk of Train – a 1D roguelike drawn in one terminal font

Hacker News

THE 23:40 SERVICE TO ALL STATIONS IS NOW BOARDING. This train is formed of twelve coaches. One of them is dark. Customers are reminded that the roof is not a designated walking route. We apologise for the delay. It has been about eighteen months. Anyway — I finished a game. It's a roguelike that takes place entirely on the roof of a night train, and the announcer talks like that for the whole thing. Ten minutes a run, plays right in the browser.

Visit product View on Hacker NewsAug 28, 2026

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Actual performance

2points

3comments

Did not reach leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

71%71% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: month, way · Missing: mobile apps, ios, personal

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

30%30% predicted probability of success on BetaList, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

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