You can skip the text and go straight to the TLDR sections to see a summary of the results. My results mostly agree with the idea that Jumping is better up to ~200k stats, then switching to energy-based training is more effective. All of the data is simulated using the new Gym gains formula with stat cap removed.

The recent changes to gym gains have brought new attention to training in general. As a returning Torn resident after an extended break, i have been wondering what is the best training method for me to grow fast to be able to participate in Ranked Wars and fun daily Torn activities (like mugging and bounty hunting). An issue is that there are so many ways to train and so many threads claiming to describe the best method, one can easily get confused. As a data-driven person, i decided to compare these methods for myself and pick what’s best for me. In this post, i will share my findings which will hopefully help you decide on how to train.

A huge shoutout goes to Vladar et al. for their work in deciphering the gym training formula, without which none of this could have been possible. If you want to play around and test things for yourself (or find and point out the mistakes i made here :P), here is a link to the R code to reproduce these calculations. If you don’t like looking at lines of code, i have also created an interactive Gym Gains Calculator (once again based on Vladar’s work), which also includes a tool to estimate gains over a time period, or the time it would take you to reach a certain goal using a defined training method- Torn-UI.

The Tests

Here is our average Joe with no life outside of Torn and no concern for his health:
- Subscriber status (150 base E, 720 natural daily E)
- Living in PI without yacht (4525 base happy, 2% gains bonus)
- Sleep is for the weak, can train 24/7
- No additional Job, Faction, Education or Book bonus
- Using refills daily (+150 E daily)
- All trains are done on Dex (just because) in George's gym (10 E per train)
- Training is done for 60 days consistently (as many trains as cooldowns allow)
- All training is simulated with 4 different starting stat values: 10k, 300k, 5mil, 100mil

Here are the Jump types included in the analysis along with some reasoning how and why some choices were made.

Classic Happy jump
4x Xanax + 5x EDVD + Ecstasy + Refill = 32h CD (one train every 1.5 days)
- Energy: 1000
- Happy: 34050
- Cost per train: ~22mil
- Number of trains: 40
- Total cost: 880mil

Classic Happy jump: Adult Novelties
* Double happy from EDVDs
4x Xanax + 5x EDVD + Ecstasy + Refill = 32h CD (one train every 1.5 days)
- Energy: 1150
- Happy: 59050
- Cost per train: ~22mil
- Number of trains: 40
- Total cost: 880mil

Single choco jump
1x Xanax + 48x Big Boxes of Chocolate + Ecstasy + Refill = 24h CD (one train per day)
- Energy: 550
- Happy: 12410
- Cost per train: ~2.4mil
- Number of trains: 60
- Total cost: 144mil

Half choco jump
1x Xanax + 24x Big Boxes of Chocolate + Ecstasy + Refill(*) = 12h CD (two trains per day)
* Since you can refill energy with points only once per day, i will split the energy gain over both jumps
- Energy: 475
- Happy: 10730
- Cost per train: ~1mil + daily refill
- Number of trains: 120
- Total cost: 120mil + 60x Refill = 188mil

Energy training
Energy training is very hard to put into exact formulas, because there are many ways to go about it.
You can waste a bit of E regen and time Xanax with max E for optimal Happy, you can ignore Happy and just spam E on cooldown, you can include FHCs in your ration to get even more E, etc. I will not even consider the can of worms that is E cans here (hehe, see what i did there?).

Energy training: 3x Xanax
* For simplicity, let's say you train every 5 hours for natural regen + one refill and split the xanax gains evenly
3x Xanax + 750 natural regen + 150 refill = 6 trains per day
- Energy: 270 (average)
- Happy: 4525
- Cost per train: ~600k
- Number of trains: 360
- Total cost: 216mil

Energy training: 2x Xanax (more chill approach)
* For simplicity, let's say you train every 5 hours for natural regen + one refill and split the xanax gains evenly
2x Xanax + 750 natural regen + 150 refill = 6 trains per day
- Energy: 230 (average)
- Happy: 4525
- Cost per train: ~470k
- Number of trains: 360
- Total cost: 170mil

Energy training: FHC (extreme case)
* In this case, we split the E gain from FHCs over all 6 trains, but ignore the happy gain
If you are using FHCs for training, the extra amount of happy is pretty much pointless at this point.
3x Xanax + 720 natural regen + 4x FHC + 150 refill = 6 trains per day
- Energy: 370 (average)
- Happy: 4525
- Cost per train: ~10.6mil
- Number of trains: 360
- Total cost: 3.8bil

The Results

Energy training with FHC is clearly providing the largest gains, followed by the other two Energy training methods. Surprisingly, the higher your starting stat is, the more viable Half Choco jumping becomes, even passing Happy jumping at some point.



Stat gains after 60 days of consistent training with different starting stat values.

While FHC training looks nice, it is an extreme scenario for this thread, so let’s look at the other methods without the FHC training:



Stat gains after 60 days of consistent training with different starting stat values. FHC training excluded for clarity.

Without the expensive FHC method cluttering our results, we can clearly see that if you start Jumping early and do it consistently, Happy jumps will provide you the fastest growth up to a certain point (eventually Energy training will catch up regardless). However, if you are starting out with a decently high stat already (300k+), Jump training is actually not that great and over the 60 days of training, Energy training methods are the clear winners. When we reach the millions, the gap between Energy training and Jump training grows wider and is pretty evident. Interestingly, Half Choco jump takes third place and even outperforms the buffed up Happy jumps! This actually becomes less surprising, when we look at how gains depend on Happy vs Energy at different starting points.


Gains after simulating training using different methods for a fixed duration (the time it takes to finish a Happy jump). Rectangle highlights the sweetspot to switch from Jumps to Energy based training. Red dot shows where Half choco jumps surpass Happy jumps.

If we simulate training over a fixed time period (the time it takes to do a happy jump in this case) using the most practical methods, we can try and determine the exact moment when Energy outweighs Happy. Switching from Jump training to Energy based training is best around 250-400k stat. If you insist on jumping, then Half-Choco jumps become more efficient at around 1.2mil stat. Only exception is if you are working in an AN company - in that case, Happy jumping offers the best gains up to ~900k stat.

TLDR: If you are just starting out, Jumping is a great way to reach the level where pure energy training is better. Value of Happy is linear, while gains from additional Energy spent are almost exponential. If your stats are close to 200k, you should consider dropping jumps and focus on energy training instead. To get even more gains, use the free booster cooldown for E items (Cans or FHC).
Or just drink beer and do crimes :)

Short note on value

Naturally, people might have different goals and different resources. Looking at the value of each method (stat % gained per $ spent), we see an interesting image:


Gains and Value (% gain per $ spent) for each training after 60 days. Value is multiplied by 1 billion to bring to scale (actual values not shown).

FHC energy training provides best gains, but is absurdly expensive. Best value option is to do 3 or 2 Xanax per day training if your stat is at least 250k. Jumping is a great way to grow early on, before you reach the critical threshold of 250k. Happy jumping is faster than Half Choco jumps, but not by that much when you factor in the cost.

TLDR: Do Half Choco jumps up to ~200k stat value, then switch to pure energy training (at least 2 Xanax/day). This provides the best bang-for-your-buck and allows for maximum flexibility in terms of timing your trains.

Links and resources:
Vladar’s thread
Happy jump guide
Choco jump guide
for the code (didn’t want to mix work and freetime in github, sorry)
Torn-UI (self-plug)

If you have any questions, suggestions or see some obvious glaring errors, you are more than welcome to point them out so i can fix them and update the results. I know that this thread does not introduce any ground breaking insights, i just thought it would be nice to have these things clearly put in one place with actual data (even though simulated) backing it up.

Omanpx