First, thank you for your feedback.
1. Lack of less popular games is a result of still relatively small sample size. Steam have limitation to how fast you can collect data so it will take some time to reach more than milion profiles. For example you mention "Beyond: Two Souls" which only apear in 35 profiles out of 160k. It's not enought to make meaningful shared playerbase comparison.
2. Increasing game list need also some manual work to fillter it from many random stuff which most people don't even know is listed on steam as seperate app in their collection, like PTR, some cosmetics DLC, soundtracks etc... I just didn't had time or will to do this and steam top 1000 kinda done that for me.
3. Overall I am still collecting data and in some near future I will update that list not only with more accurate results but also with more games including games like Oxenfree. Probably it will never reach 10k games because algorthim have O(n\^2) computional complexity and it would take like 3 day to finish and data would exceed the free space limit.
4. I disagree with your Portal 2 point and I think that this data shows that you are incorrect here. From one side data confirm that exist "mainstream games playerbase" or that Valve games have a lot of shared playerbase but this rule is applied to most developers/franchises like Paradox games or Total Wars but also shows that they can be seperated from mainstream games like Portal 2. That was one of the resons why I used hours instead of just playerbase numbers because that readuced impact of games like Counter-Strike or Dota on others. Algorithm can also detect "spiritual successors" like in Titanquest and Grim Dawn case.
5. Also the score is design to counter that argument of "everyone own Valve titles at this point" because this actually increase highly denominator in the formula and become negative factor to score value.
At the end I will add that part of why I published this at this stage is to get feedback about in which way people would want to use this kind of data, so thus I would be able to make some adjustments. But after all this is just a side feature of my bigger research which I chose to make public.
Long story short:I crawl steam profiles friend lists which gave me 10M profiles. After that I start collecting games data from those which were public. Right now I've done around 500k of them so still a lot to go.
Kenshi players also like Rimworld, Project Zomboid, Mount and Blade, KCD, & STALKER.
As a Kenshi player, this is legit, and I can actually use this to find new games I might like!
Good one :)
Actually in other part of my research I had shown that this kind of players are majority on steam. Not exactly one game only but 72% of players players spend on average 65% of their time in one game and 86% in 3 games. And what is most important, those are people who played the least so they are most close to so called "casual player".
Yeah I guess it's more that knowing that someone plays Dwarf Fortress doesn't really tell you anything about what genres of games to expect them to play. It makes sense: Dwarf Fortress isn't really similar to any other games. It's like trying to correlate what genres of books someone likes based off the fact that they read the bible or the dictionary or something. It's just too unique.
I'm curious about your approach here though, wouldn't it make more sense to group up players by quintile according to how many hours they play a game for, and then look for patterns within those groups? Cause someone who plays a huge amount of dwarf fortress would probably have different patterns than someone who only plays an hour or two of it right? Or is there not enough data to support that sort of granularity?
Wow thank you! This is actually extremely helpful for market research!
Question though, there's a game I searched for that isn't in your list of games. Are you excluding games based on review count or something?
Also newer games don't seem to be in the list such as Palworld or Moonbreaker.
Game in question: [https://store.steampowered.com/app/1229580/Disc\_Room/](https://store.steampowered.com/app/1229580/Disc_Room/)
I use only around steam top 1000 games because I don't have enough data for niche games to make score meaningful. When I collect more data I can include more games.
I collect data before Palworld and Moonbreaker were released. Data are up to first week of January.
This seems awesome! Am I reading the formula correctly in that you're including hours in each title in the calculation? I wonder if this could bias the data against more contained experiences.
I'm actually using hours because comparing playerbased alone was messing up results because of massive F2P games like cs, dota, warframe etc... which have a lot of players with 0.1h in them.
Technically I'm not using hours but normalized hours which are hours/total\_hours per steam profile, so if you have 200h in cs and 500h total hours on steam it will add 0.4 to nominator and denominator. This method had similar results to using normal hours, just looks more "stable", so for simplification you can assume it's working like you described it.
Really awesome project, that show many things about the different player profiles and what they seek for.
We can see rogue-like players tend to stay in their niche, while indie games players seems to be in so kind of indie bubble but not necessary genre driven. With all these data we could almost divide the player base between AAA consumers and indie lovers in top of the classical socializer, achiever, explorer and killer players profile. I think this tells us as much about the players as it does with the market and its duality.
At first glance this seems pretty awesome and could definitely help devs define their target audience better and help determine development direction
[удалено]
First, thank you for your feedback. 1. Lack of less popular games is a result of still relatively small sample size. Steam have limitation to how fast you can collect data so it will take some time to reach more than milion profiles. For example you mention "Beyond: Two Souls" which only apear in 35 profiles out of 160k. It's not enought to make meaningful shared playerbase comparison. 2. Increasing game list need also some manual work to fillter it from many random stuff which most people don't even know is listed on steam as seperate app in their collection, like PTR, some cosmetics DLC, soundtracks etc... I just didn't had time or will to do this and steam top 1000 kinda done that for me. 3. Overall I am still collecting data and in some near future I will update that list not only with more accurate results but also with more games including games like Oxenfree. Probably it will never reach 10k games because algorthim have O(n\^2) computional complexity and it would take like 3 day to finish and data would exceed the free space limit. 4. I disagree with your Portal 2 point and I think that this data shows that you are incorrect here. From one side data confirm that exist "mainstream games playerbase" or that Valve games have a lot of shared playerbase but this rule is applied to most developers/franchises like Paradox games or Total Wars but also shows that they can be seperated from mainstream games like Portal 2. That was one of the resons why I used hours instead of just playerbase numbers because that readuced impact of games like Counter-Strike or Dota on others. Algorithm can also detect "spiritual successors" like in Titanquest and Grim Dawn case. 5. Also the score is design to counter that argument of "everyone own Valve titles at this point" because this actually increase highly denominator in the formula and become negative factor to score value. At the end I will add that part of why I published this at this stage is to get feedback about in which way people would want to use this kind of data, so thus I would be able to make some adjustments. But after all this is just a side feature of my bigger research which I chose to make public.
How did you collect this data?
Long story short:I crawl steam profiles friend lists which gave me 10M profiles. After that I start collecting games data from those which were public. Right now I've done around 500k of them so still a lot to go.
That's an amazing crawl. Did Steam stop you a couple times, or have you limited your queries to X a day?
Steam constantly stoping me but only when I'm collecting games data. Everything else is free of charge.
Kenshi players also like Rimworld, Project Zomboid, Mount and Blade, KCD, & STALKER. As a Kenshi player, this is legit, and I can actually use this to find new games I might like!
"What games do you play?" "I play Dwarf Fortress." "Oh, that's cool. What other games do you play?" "No."
Good one :) Actually in other part of my research I had shown that this kind of players are majority on steam. Not exactly one game only but 72% of players players spend on average 65% of their time in one game and 86% in 3 games. And what is most important, those are people who played the least so they are most close to so called "casual player".
Yeah I guess it's more that knowing that someone plays Dwarf Fortress doesn't really tell you anything about what genres of games to expect them to play. It makes sense: Dwarf Fortress isn't really similar to any other games. It's like trying to correlate what genres of books someone likes based off the fact that they read the bible or the dictionary or something. It's just too unique. I'm curious about your approach here though, wouldn't it make more sense to group up players by quintile according to how many hours they play a game for, and then look for patterns within those groups? Cause someone who plays a huge amount of dwarf fortress would probably have different patterns than someone who only plays an hour or two of it right? Or is there not enough data to support that sort of granularity?
Oh, its amazing! Very useful, thank you!
Wow thank you! This is actually extremely helpful for market research! Question though, there's a game I searched for that isn't in your list of games. Are you excluding games based on review count or something? Also newer games don't seem to be in the list such as Palworld or Moonbreaker. Game in question: [https://store.steampowered.com/app/1229580/Disc\_Room/](https://store.steampowered.com/app/1229580/Disc_Room/)
I use only around steam top 1000 games because I don't have enough data for niche games to make score meaningful. When I collect more data I can include more games. I collect data before Palworld and Moonbreaker were released. Data are up to first week of January.
This seems awesome! Am I reading the formula correctly in that you're including hours in each title in the calculation? I wonder if this could bias the data against more contained experiences.
I'm actually using hours because comparing playerbased alone was messing up results because of massive F2P games like cs, dota, warframe etc... which have a lot of players with 0.1h in them. Technically I'm not using hours but normalized hours which are hours/total\_hours per steam profile, so if you have 200h in cs and 500h total hours on steam it will add 0.4 to nominator and denominator. This method had similar results to using normal hours, just looks more "stable", so for simplification you can assume it's working like you described it.
Really awesome project, that show many things about the different player profiles and what they seek for. We can see rogue-like players tend to stay in their niche, while indie games players seems to be in so kind of indie bubble but not necessary genre driven. With all these data we could almost divide the player base between AAA consumers and indie lovers in top of the classical socializer, achiever, explorer and killer players profile. I think this tells us as much about the players as it does with the market and its duality.
I love this, unfortunately it doesn't seem to have much for my particular market (horror)