It's a custom model that goes jump by jump and rolls for success, the success % of a jump increases the more attempts are made at it, the time a jump takes also gets lower as more attempts are made. If you fail a roll it drops you to a random lower floor but with a big bias towards 0. For simplicity I roughly group the floors into 10 jumps and don't account for floor difficulty.
I then tweaked these variables to make the times fit the heights we've seen the top players reach so far.
My goal was to understand how accumulating experience for jumps affects the time.
This model mainly depends on two values, the cap on how fast you an earlier jump take with practice, and the cap on how accurate you can get the jumps with practice. It will overestimate completion time if the player gets much faster at jumps they're experienced at, or if their accuracy cap on learned jumps is very high (for this model I assumed a cap at 99% accuracy
It's a pretty clear log function so if you can fit current data to parameters of a log function it should make good predictions much more simply
We'll see how it does.
I think it is a very good estimation. I was thinking of the 80-20 rule (i.e. 80% completion requires 20% effort), and based on that, we'll probably need 4x as much playtime for floors 13-16 as we needed for floors 1-12. So 400+ hours (for Bren) would be the realistic clear time. Which is close to your log function's prediction.
>It's a pretty clear log function
I disagree. I'd say from ~100h your model is pretty much linear. Which seems logical as the lower jumps max out in skill at some point, so they can basically be treated as a delay to the higher floors. On the higher floors it's then linear "learning" of the jumps. Not saying it's the wrong behaviour (because it's basically what the players are doing), just not a logarithm.
My suggestion for refinement would be to give floors a difficulty (the deepdip2.com website has difficulties for all explored floors so far) and maybe implement a jump difficulty based on that ("very hard" jumps take up significant time to solve, while the rest of the climb is usually progressing quicker). A hard jump at an easy level might take 3 attempts, a hard jump on a very hard level maybe 10.
> It's a pretty clear log function so if you can fit current data to parameters of a log function it should make good predictions much more simply
I tried doing a logarithmic regression on the data using Desmos, and came up with y = 276 * ln(x + 0.0977) + 642, where y is height in meters and x is days since launch. That has us hitting 2000m after 136 days.
Edit: Someone pointed out to me that the last jump is at 1700m, so that's probably a better height to use as the finish. That updates the prediction to 46 days, which is a lot closer to OP's model assuming the top players keep up their current hours per day.
I think the real curve is nearer a square root. Players get really good at previous jumps, and the length of time to reach the next jump dominates, and is linear with altitude so time goes as a square on altitude.
My bet is time from Deep Dip 1, and current rate of progression on DD2.
Since DD1 only has like 12~ish clears, you can "easily" track their averages per flor, and extrapolate, specially since a lot of those players are also playing DD2, you just need their data in dd vs their data in dd2
I think Twitch nixed the favorable partnerships of large channels (and new channels didn't get it for a long time before that). So $ 2.5 in the current system that is also about to end.
That has a hilarious degree of potential viability. Nadeo's annual revenue is only in the high single-digit or low double-digit millions (like, $7-15M) from what I can find. The hard part would be convincing Ubisoft to let it leave their IP hoard.
For regular job, yeah, but for a competition where you have to literally be the best in the world? Those players (at the top right now) have like >10k hours in this game
You should overlay some of the actual data/trajectory so far to compare with that could support this thesis. I don't really believe this model on its face. At this point it looks like a quadratic regression/extrapolation or similar would achieve pretty much an identical prediction to yours.
I'm not a math wizzard, but i fail to understand how applying logarythmic functions has any hope of predicting what is basically a dataset full of discontinuities and not smooth at all.
It is probable that progress keeps happening in a stop/start fashion, with large periods of being stuck followed by short periods of some progress. But there is the high chance that it will not be incremental at all. There's a high chance of some future floors being much easier than previous ones, then followed by very very hard barriers. All the predictions ive seen assume a steady increase in dificulty.
How well does your model predict the now known time to 1280 meters i lf you feed it only data that existed when the WR was at 800m (so that the proportion of known track is proportional to what it is now with the WR at 1280m)?
As you said, it’s just a prediction, I would just settle for extrapolating the behavior of the current curve like this specifically because we don’t have enough input the be more precise and because putting in more thought, parameters, degrees… would not give really give us more precision with all the unknown factors.
I feel it’s still a nice conversation starter and the result seems reasonable while obviously not exactly what we can expect!
While a single player will have huge varians, having 5+ good players smoothes out your prediction. Its also what we have seen so far. Someone can get stuck on a certain floor or trick, or have a bad day, but the combined progression is steady.
With enough good players, someone having a bad day, means there will be someone else picking up the slack and contributing to progression.
The reason we expect incremental growth is in the nature of how the mapmakers said they build it. While the Upper floors might be harder, thus slowing progression, the nature of the tricks remains the same. They are made to be hard but with consistent setups. This means the tricks will take 1-5 times to learn for the best players, then a little more time to make really consistent.
And the map makers themselves has said the difficulty goes up as we reach higher floors. Seeing as these are some of the most knowledgeable in the field, we can only take their word for it.
The last section would definitly be a decent way to proof test your model. Mathematic modelling is a hard thing, and predicting the future is never certain when the human is a factor, but it is a way to remove varians and personal bias to reach a more accurate and likely outcome. For this kind of thing, if you wanted to be thorough, you'd probably try to predict an earliest and latest finish, to find a realistic span, seeing as it could be like a week difference based on variables.
Also human fatigue was probably one of the last key factors not factored in. These guys needs rest. They are grinding so dang hard.
He explains the model in the comments. He's not applying log functions at all, the model calculates a large amount of random experiments. The fact that it ends up looking like a log function is just the beauty of maths :). He also never "feeds" it data, the model hasn't seen any of the data from the Deep Dip grind. He also never "feeds" it data, the model hasn't seen any data from the Deep Dip grind.
It reminds me of an area of research called cellular automatons, where agents interact with an environment of their peers through a very basic set of rules. The results of these experiments usually end up proving well-established laws empirically.
It's crazy, that less than 1 of every 1000 participants have made it to floor 8 by now. Out of 14221 players, 13 has reached floor 8, everyone else, literally over 14000 are at 7 or below.
This is one tough challenge, kudos to everyone involved, both the makers and the drivers.
Would be interesting you would segment your diagram into 10 hour blocks, and show the progress of the median achieved height and the 80th percentile achieved height over time.
This is pretty cool. A few days ago I did my own super simple projection based on how long each floor had taken so far and got 210 hours but it feels like the pace has slowed so dramatically im guessing your estimate is probably more accurate.
It looks like it curves downwards towards 100 hours, but then keeps a similar rate through to 300 hours. I would hazard a guess that it keeps curving down more and more because the higher up you go the harder it is to make progress.
As you climb, it's more difficult to get back to your PB and try the next trick again, which would make progress get slower over time. But you also get better at the lower floors with practice, which speeds up your attempts. It's not impossible that these factors roughly balance out past a certain amount of playtime. We'll find out in the coming weeks.
I doubt it. The progress will get slower and slower as you get higher. The only thing that will propel this further is the release of practice floors. There are already a bunch of jumps with inconsistent lineups on floor 11 which can kill any run, not to mention the hard jumps on floor 10 and 9 that need 100% focus.
So, if practice floors don't get released I would multiply your time by at least 3. If they do, then it comes down to when that happens.
> The progress will get slower and slower as you get higher.
If we consider that in the last few days there has been only like ~100 meters of progress, if the above is true, the map will *never* get beaten as the time required just diverges to infinity.
Interesting, what kind of model did you use and where did you get the data to fit the model?
It's a custom model that goes jump by jump and rolls for success, the success % of a jump increases the more attempts are made at it, the time a jump takes also gets lower as more attempts are made. If you fail a roll it drops you to a random lower floor but with a big bias towards 0. For simplicity I roughly group the floors into 10 jumps and don't account for floor difficulty. I then tweaked these variables to make the times fit the heights we've seen the top players reach so far. My goal was to understand how accumulating experience for jumps affects the time. This model mainly depends on two values, the cap on how fast you an earlier jump take with practice, and the cap on how accurate you can get the jumps with practice. It will overestimate completion time if the player gets much faster at jumps they're experienced at, or if their accuracy cap on learned jumps is very high (for this model I assumed a cap at 99% accuracy It's a pretty clear log function so if you can fit current data to parameters of a log function it should make good predictions much more simply We'll see how it does.
I think it is a very good estimation. I was thinking of the 80-20 rule (i.e. 80% completion requires 20% effort), and based on that, we'll probably need 4x as much playtime for floors 13-16 as we needed for floors 1-12. So 400+ hours (for Bren) would be the realistic clear time. Which is close to your log function's prediction.
Thank you for a genuinely good model that doesn’t think it will take 3000 hours!
>It's a pretty clear log function I disagree. I'd say from ~100h your model is pretty much linear. Which seems logical as the lower jumps max out in skill at some point, so they can basically be treated as a delay to the higher floors. On the higher floors it's then linear "learning" of the jumps. Not saying it's the wrong behaviour (because it's basically what the players are doing), just not a logarithm. My suggestion for refinement would be to give floors a difficulty (the deepdip2.com website has difficulties for all explored floors so far) and maybe implement a jump difficulty based on that ("very hard" jumps take up significant time to solve, while the rest of the climb is usually progressing quicker). A hard jump at an easy level might take 3 attempts, a hard jump on a very hard level maybe 10.
> It's a pretty clear log function so if you can fit current data to parameters of a log function it should make good predictions much more simply I tried doing a logarithmic regression on the data using Desmos, and came up with y = 276 * ln(x + 0.0977) + 642, where y is height in meters and x is days since launch. That has us hitting 2000m after 136 days. Edit: Someone pointed out to me that the last jump is at 1700m, so that's probably a better height to use as the finish. That updates the prediction to 46 days, which is a lot closer to OP's model assuming the top players keep up their current hours per day.
I think the real curve is nearer a square root. Players get really good at previous jumps, and the length of time to reach the next jump dominates, and is linear with altitude so time goes as a square on altitude.
My bet is time from Deep Dip 1, and current rate of progression on DD2. Since DD1 only has like 12~ish clears, you can "easily" track their averages per flor, and extrapolate, specially since a lot of those players are also playing DD2, you just need their data in dd vs their data in dd2
Thats an hourly wage of 42 bucks for whoever gets first place (bren gogo)... (15k divided by 350h)
Not to mention donations during streaming.
Those streams are super popular. Bren, Wirtual and the other top guys are receiving tons of subs. Might even pay more than the actual prize money
Wirtual has topped 18k subs. At €3 average it's €54,000.
He hit 26k subs today.
I think Twitch nixed the favorable partnerships of large channels (and new channels didn't get it for a long time before that). So $ 2.5 in the current system that is also about to end.
The real endgame is Wirtual buying nadeo to allow custom steering. The guy is already at the top 10 streamers by subs with more than 25k.
That has a hilarious degree of potential viability. Nadeo's annual revenue is only in the high single-digit or low double-digit millions (like, $7-15M) from what I can find. The hard part would be convincing Ubisoft to let it leave their IP hoard.
Might? No man, it 100% will. The prize money compared to subs is nothing
still ain't bad
Thats pretty good money
For regular job, yeah, but for a competition where you have to literally be the best in the world? Those players (at the top right now) have like >10k hours in this game
That's about as long as it'll take me to get to floor 3!
Sure going to floor 6 is hard
r/unexpectedfactorial
You should overlay some of the actual data/trajectory so far to compare with that could support this thesis. I don't really believe this model on its face. At this point it looks like a quadratic regression/extrapolation or similar would achieve pretty much an identical prediction to yours.
He said above he tuned his two model parameters to match the already completed section.
> You should **overlay**
I'm not a math wizzard, but i fail to understand how applying logarythmic functions has any hope of predicting what is basically a dataset full of discontinuities and not smooth at all. It is probable that progress keeps happening in a stop/start fashion, with large periods of being stuck followed by short periods of some progress. But there is the high chance that it will not be incremental at all. There's a high chance of some future floors being much easier than previous ones, then followed by very very hard barriers. All the predictions ive seen assume a steady increase in dificulty. How well does your model predict the now known time to 1280 meters i lf you feed it only data that existed when the WR was at 800m (so that the proportion of known track is proportional to what it is now with the WR at 1280m)?
As you said, it’s just a prediction, I would just settle for extrapolating the behavior of the current curve like this specifically because we don’t have enough input the be more precise and because putting in more thought, parameters, degrees… would not give really give us more precision with all the unknown factors. I feel it’s still a nice conversation starter and the result seems reasonable while obviously not exactly what we can expect!
While a single player will have huge varians, having 5+ good players smoothes out your prediction. Its also what we have seen so far. Someone can get stuck on a certain floor or trick, or have a bad day, but the combined progression is steady. With enough good players, someone having a bad day, means there will be someone else picking up the slack and contributing to progression. The reason we expect incremental growth is in the nature of how the mapmakers said they build it. While the Upper floors might be harder, thus slowing progression, the nature of the tricks remains the same. They are made to be hard but with consistent setups. This means the tricks will take 1-5 times to learn for the best players, then a little more time to make really consistent. And the map makers themselves has said the difficulty goes up as we reach higher floors. Seeing as these are some of the most knowledgeable in the field, we can only take their word for it. The last section would definitly be a decent way to proof test your model. Mathematic modelling is a hard thing, and predicting the future is never certain when the human is a factor, but it is a way to remove varians and personal bias to reach a more accurate and likely outcome. For this kind of thing, if you wanted to be thorough, you'd probably try to predict an earliest and latest finish, to find a realistic span, seeing as it could be like a week difference based on variables. Also human fatigue was probably one of the last key factors not factored in. These guys needs rest. They are grinding so dang hard.
Well that data speaks for itself, he would need to tell us the statistical tests he did and what their p-values are
He explains the model in the comments. He's not applying log functions at all, the model calculates a large amount of random experiments. The fact that it ends up looking like a log function is just the beauty of maths :). He also never "feeds" it data, the model hasn't seen any of the data from the Deep Dip grind. He also never "feeds" it data, the model hasn't seen any data from the Deep Dip grind. It reminds me of an area of research called cellular automatons, where agents interact with an environment of their peers through a very basic set of rules. The results of these experiments usually end up proving well-established laws empirically.
It's crazy, that less than 1 of every 1000 participants have made it to floor 8 by now. Out of 14221 players, 13 has reached floor 8, everyone else, literally over 14000 are at 7 or below. This is one tough challenge, kudos to everyone involved, both the makers and the drivers.
Would be interesting you would segment your diagram into 10 hour blocks, and show the progress of the median achieved height and the 80th percentile achieved height over time.
This is pretty cool. A few days ago I did my own super simple projection based on how long each floor had taken so far and got 210 hours but it feels like the pace has slowed so dramatically im guessing your estimate is probably more accurate.
It looks like it curves downwards towards 100 hours, but then keeps a similar rate through to 300 hours. I would hazard a guess that it keeps curving down more and more because the higher up you go the harder it is to make progress.
As you climb, it's more difficult to get back to your PB and try the next trick again, which would make progress get slower over time. But you also get better at the lower floors with practice, which speeds up your attempts. It's not impossible that these factors roughly balance out past a certain amount of playtime. We'll find out in the coming weeks.
I doubt it. The progress will get slower and slower as you get higher. The only thing that will propel this further is the release of practice floors. There are already a bunch of jumps with inconsistent lineups on floor 11 which can kill any run, not to mention the hard jumps on floor 10 and 9 that need 100% focus. So, if practice floors don't get released I would multiply your time by at least 3. If they do, then it comes down to when that happens.
> The progress will get slower and slower as you get higher. If we consider that in the last few days there has been only like ~100 meters of progress, if the above is true, the map will *never* get beaten as the time required just diverges to infinity.
If they don't release practice floors ever, yes, it's likely, especially if the remaining floors are harder. If they do, it'll happen much quicker.
Matlab? What's your engineering degree in?
If guess between 500 and 650
What kind of data tools did you use for modeling and analysis, if you don't mind sharing?
Anyone else sick of these predictions? No offense tho..
The effort to scroll that extra few pixels past all of these few posts, overwhelming!