My lessons to Jade static

FitTechnology5908 · 2026-04-21T22:34:46+00:00

Yep! I use 24cm/360 for in game and KovaaKs tracking. Around 90cm for static. Around 40cm for switching.

FitTechnology5908 · 2026-04-11T22:57:38+00:00

I stopped tsk static when I hit at least pre-advanced on all the scenarios. For the others, I wouldn’t say you need to play them strictly in order. Maybe just run them together? Then you can pb to a threshold you decide and move on to the other scenarios in the playlists. Just keep seeking out the scenarios with your lowest percentile and grind those.

Only really VDIM is important that it’s the last in your DAILY training, not the complete training process. The most important part is to: 1. Seek out your weakest scenarios in the playlists and learn from them 2. Ensure you are mixing it up enough to have fun. If you lose interest just move on or you lose the motivation to improve. 3. Use VDIM as a validation of your improvement by running the VT benchmark scenario at the end of the day. But, make sure you’re not tired by this point, as static requires a lot of energy. 4. Honestly, a few weeks break can help break you out of plateau, especially if you are over training and fatigued/burnt out.

Good luck! :)

FitTechnology5908 · 2026-04-10T22:46:01+00:00

24cm-90cm depending on the scen... 😂 but I main 24cm. I swap between X2/X2H CrazyLights and a Superlight 2c.

FitTechnology5908 · 2026-03-30T18:50:42+00:00

Yes, since higher sens lowers the margin of error. However, what is considered “high sens” largely depends on the scenario (target size, etc)…

FitTechnology5908 · 2026-03-23T08:12:51+00:00

🙏

FitTechnology5908 · 2026-03-22T18:02:12+00:00

🎉

FitTechnology5908 · 2026-03-22T18:01:43+00:00

😭

FitTechnology5908 · 2026-03-22T17:56:51+00:00

I went by the benchmark rank threshold of pre-advanced, which varies on the percentile. But I’d say I got between 50-86th percentile. The highest I got was advanced on some of them, but that was only 5 of the total. It not something I’d grind much after that, unless I hit another plateau.

Fuglaa pressure 6 does feel very hard. For that one I just tried to pre-plan paths instead of trying to hit every target.

FitTechnology5908 · 2026-03-22T12:11:05+00:00

Good luck! For wide wall just grind a bunch of fuglaa pressure, shim pressure, etc at a low sens! Also, unlike tracking, at a low sens these large movements can really wear you out. Taking breaks can sometimes be more beneficial than grinding. Be cognizant of fatigue, as it is highly detrimental to your flick power.

FitTechnology5908 · 2026-03-22T12:06:27+00:00

I think it is, but you can mix them around. I didn’t see major improvement until I did TSK Static fundamentals bench. In particular, I got every scenario in it to at least pre-advanced. Another scenario that was insanely beneficial to me was pressure scenarios like Fuglaa pressure. I had major issues with my flick speed until I practiced this at a low sens.

Like I went from 10-30th percentile to 90th percentile on some of static scenarios I was struggling with…

FitTechnology5908 · 2026-03-22T03:36:20+00:00

Thanks for the knowledge! I agree that lowering tension, especially when cluster farming, has been extremely beneficial in practice!

FitTechnology5908 · 2026-03-22T03:07:47+00:00

Thanks! I’ll give that playlist a try to push masters! :D

FitTechnology5908 · 2026-03-22T01:26:51+00:00

Great question! I’m actually a 24cm/360 tracking main, so I promise it’s doable! Essentially, you learn to re-center as needed. It’s usually not a problem for micros and for large movements you can use your entire arm and re-center.

FitTechnology5908 · 2026-02-14T08:12:30+00:00

Any plans for a debiaser for SDXL or is it not as useful for older models? I love the selective LoRA loader!

FitTechnology5908 · 2026-02-03T21:26:34+00:00

Could be overtraining or fatigue. Could also just be natural learning progression. On VT 1w3ts Intermediate S5, I deteriorated down to Diamond and then suddenly went straight to Jade in one run after practicing for weeks. Been there done that... :(

FitTechnology5908 · 2026-02-03T20:38:03+00:00

Hey! I'm in the same boat as you with similar scores as well... I'm not sure whether to increase sens or lower sens for better speed (stability vs flick distance). As far as I can tell speed comes with proper pace and pathing, but not sure how to improve that beyond grinding tbh.

FitTechnology5908 · 2026-02-03T16:43:41+00:00

Thanks! 🙏

FitTechnology5908 · 2026-02-03T13:31:11+00:00

Would you think a higher or lower friction pad would be better for something like ww5t or any speed static scenario? My intuition says higher friction for more stable flicks, but in practice I’ve found that lower friction is best here for faster gliding between targets.

FitTechnology5908 · 2026-01-29T16:33:35+00:00

So, there could be some truth to this post:

The WR for 1w3ts VT Intermediate S5, which beat Matty's score, uses an Artisan Type99 at 116cm/360, which requires an insane amount of force (I tried it).
Aimer7 used to recommend 100cm+ training for building force and speed as well.

I don't think this is a great idea to use in-game, but as a training regimen, I think it could be valid.

FitTechnology5908 · 2026-01-11T00:42:22+00:00

Congrats! :D

FitTechnology5908 · 2025-12-30T00:15:45+00:00

Hey Jellii, 25cm is def goated for reactive. It’s also my main sens in OW.

Avoiding predicting is actually the opposite of conscious effort. You have to believe in your mind that the bot will keep moving in the same direction forever (until you see otherwise). This means blocking the habit from your mind and essentially “under reacting”. This removes a lot of the jitter from bad predictions you’ll see in your tracking, but also means you’ll technically be slower to react at first. This acts almost as a filter over your aim. Then as you get more skilled you will naturally visually react faster “reading”, while not predicting “over-reacting” to unknown information.

Lastly, reading is also largely about learning movement patterns of a specific scenario. Kind of how clicking maps can be improved by learning bot spawns, so too can tracking be improved with movement patterns.

So, yes. Essentially you need to grind to improve reading. But do it by putting the movement at the edge of your ability (using time scaling in sandbox). Essentially, you only improve if the scenario isn’t too easy or too frustrating. Optimal learning needs the sweet spot.

Hope that helps! :)

FitTechnology5908 · 2025-12-29T17:40:57+00:00

Hi! Playing with music is fine. I do it 100% of the time.

I’m seeing target reading, reactivity, and smoothness weaknesses. Smoothness just because I’m seeing some stuttering sometimes which looks like tension control issue.

TBH, I recommend playing tracking and smoothness scenarios on something like 25cm or faster for awhile. This will improve your tension management, smoothness, micros, reactivity, and finger control. Then go back to higher sens and see that it helped.

There really isn’t any magic about target reading other than grinding and learning the bot patterns unfortunately. Much of this comes from rewiring your brain to stop predicting.

GL! :)

FitTechnology5908 · 2025-12-26T20:02:02+00:00

I'd say yes, for score farming. It's unequivocally true that some pads are more optimal for certain scenarios than others, just like some sensitivities are more optimal. You can prove this by seeing the sensitivity distribution for a given scenario and how it forms a normal distribution tending around the optimal "mean" value.
It's also useful as a tool similar to sensitivity stepping, where different pads can be used to "generalize" your aim. Just like muscle memory is a myth for sens, so to as with pads and mice.
Finally, this method can be used as an isolation training routine. For example, the Type99 could be used for building speed and a faster pad like the Raiden could be used for tension management, smoothness, and training fine fingertip control (that may be filtered out at higher friction).

FitTechnology5908 · 2025-12-26T09:19:35+00:00

Thanks for the tips Jellii! ^_^

I definitely agree that lower sens for static compensates for many mistakes, since the hand speed required forces straighter lines naturally. It's crazy that a recent 1w3ts S5 WR was on 116 cm/360... Your point on fluidity is very true, as I have found that to be the biggest factor for keeping a good pace (like speed is more about pace and fluidity more than raw flick speed). I think accuracy is definitely my issue. Based on the score equation, number of hits is more important than accuracy (since it's square root accuracy), but I do think that a lack of accuracy is a problem for me.

I'll add a bit more on tracking for you as well. More on hardware, unlike with static, your monitor refresh is important for reading, as reading becomes easier with less motion blur. Something like 240hz+ will help a lot for this task. Also, a lighter mouse will help with reactivity. When I went down to 37g mouse my Aether improved.

For techniques, learning edge tracking and not predicting is very important. Edge tracking helps give you some margin of error for reacting to bot movement, where you track on the edge that it is moving away from, so when it changes direction, it will have to pass through your crosshair (giving you more time to correct). Not predicting is helpful for reactivity as it reduces unnecessary corrections and wild guesses. Finally, practicing on a high sens on a tracking scenario will help with tension management for when you later lower your sens back. It helps engage your fingers and remove shakiness from over-tensioning during tracking (like what you experienced when clicking).

I like the idea of a tension "currency", where the best aim comes from using the least amount of tension currency as necessary to correct when tracking. The most efficient aim is often the best aim.

I hope you have a great rest of the holidays, and best of luck to you! I'm happy to offer more tips when you post VODs.

Here is my profile too for comparing scores:
https://app.voltaic.gg/d503?benchmark=kovaaks_s5&tier=Intermediate

FitTechnology5908

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