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Video Poker Trainer

Hacker News

Video Poker Trainer

I've created a trainer for video poker based on the 99.54% RTP strategy as outlined in "The Doctrine of Chances" by Steward N. Ethier (p 554 table 17.5). Apparently the maximum RTP for video poker wasn't proven until 2010, which is astonishing to me given the game has been in the wild since 1979. Note this is a strategy for classic 9/6 Jacks or Better (Full Pay) - it does not apply to popular variants which followed. A full "cycle" in video poker from the house perspective is regarded as around 13k hands played (in which case you should see a royal flush). What I can see from the general public playing video poker over 18,471 hands is that the global RTP is 94.29% - which means the vast majority of players are using a sub-optimal strategy. This also means that 9/6 Jacks or Better was/is likely a very profitable game for land based casinos back in the day. Looking forward to any feedback!

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Actual performance

3points
2comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Strong signals: video, profitable · Missing: mobile apps, ios, personal
62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide · Missing: https docs, excited, just released
50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: using · Missing: mac, agents, macos
38%38% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: profit, profitable · Missing: arr, mrr, revenue
25%25% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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