What is score farming?
An ongoing discussion in the aim community has been the idea of score farming and playing the aim trainer specifically just to get higher scores.
I want to start off by stating that everything I’m about to go into is my opinion alone and from my perspective. However you approach training with this software is completely up to you, and no one should be allowed to dictate exactly how you do it. For anyone who isn’t aware, I am an aim training main. My main game is NOT Overwatch, despite my username, it’s not Apex, or CS, or VALORANT. It is no “real” FPS game. I play aim trainers competitively as my main focus, and anything that I do for improvement in my aim, I do solely to get better scores in the aim trainer.
So what is score farming? If it isn’t obvious from the name itself, it’s basically playing aim trainers in such a way that you are only caring about getting higher scores in scenarios. Under this definition, I am a score farmer. I change my settings within the aim trainer to make it easier for me to score higher on certain scenarios, including playing different sensitivities, changing my visuals, or switching crosshairs.
Score farming vs. Cheesing
One thing I want to get out of the way before we break this down is that score farming is fundamentally different from cheesing scenarios. What’s the difference? My definition for cheesing is when you intentionally use some strategy that undermines the purpose of the scenario. Even if it doesn’t yield a higher score, if you’re going around what the scenario is meant to test of you, that’s cheesing. Cheesing is forbidden in competitive aim training, that is, for benchmarks and aim tournaments and is generally frowned upon by the community, but I do still want to discuss them here so we know what is and is not allowed.
Two main things are considered cheesing. First up is running a lower FOV than Overwatch 103. Overwatch 103 was established as the standard in the early days of Voltaic. Running a lower 103 circumvents the precision and micro requirements of static, dynamic, speed, and smoothness scenarios. Because of how it trivializes these scenarios, it is forbidden.
Second is pausing mid-run. Pausing essentially allows you to halt the entire scenario usually to allow you to reset your mouse. Correctly utilizing mousepad space is part of the skill of aiming, especially in precise and reactive tracking. Because this takes the space management out of the task, pausing is forbidden.
Cheesing is not the focus of this video, but we should acknowledge it because using these tactics fall outside the realm of proper training, regardless of the score boost.
A case for score farming.
The main criticism against score farming is the fact that engaging in it sacrifices “real improvement” and will stifle a player’s aim development.
Firstly, and this is again coming from more of my own experience, I don’t see how optimizing for the highest scores counteracts improvement.
On well-designed scenarios, that is, ones that aren’t painfully straightforward and actually take a lot of conscious thought to perform well in, score farming has still led to me seeing significant improvement in this skill. I’ve been score farming for up to 2-3 years now, and my aim, both in-game and in the trainer, has not stopped improving.
I’ve also not adhered to any other structure or refined approach. Nor did I ever care about “aim science.” The most I ever did with a routine was the score threshold structure, which is score farming in itself.
Odds are if you’re playing good scenarios, you’re paying attention to good technique and good form, and you’re consciously trying to find ways to optimize your approach, you will improve either way.
Secondly, what we do to optimize for score in the aim trainer does not differ that much from what speedrunners do when they try to get better times for beating their respective games. Reset spamming is one commonly criticized tactic. The argument is that reset spamming makes you less skilled at aim training and hurts your development as an aimer. Is that how it works in speedrunning though? Take Minecraft speedrunning as an example. RNG is what holds us back from beating Minecraft in the lowest time. This is why speedrunners will constantly spam restart new worlds to get a better, more lucky seed. It’s the same thing with aim training. Why would you start a run with several bots offscreen? Just reset for better RNG. This makes it a more fair and equal process for all players in the scenario.
And doing this obviously doesn’t hurt our improvement. Speedrunners are some of the most skillful players in their respective games. I’d even say that if you wanted to get really good at a particular game, try speedrunning it. Actions that save time in speedrunning are almost the same thing as score farming tactics in the aim trainer.
Score farming tactics
Low Sensitivity
The first one is low sensitivity. While it’s obvious that a low sens feels more consistent and controllable, which can make a lot of scenarios feel easier, we need to consider exactly what we’re training. The arm is more stable than the wrist and fingertips, so micro jitters in smooth tracking scenarios won’t appear as pronounced. To many players, this is cheesing smoothness, but I disagree. When you run low sens, you lose a degree of mobility. You’re also still being smooth in general and focusing the skill with your arm, which isn’t circumventing the purpose of the scenario.
Edge Tracking
Next up is edge tracking. Edge tracking means to deliberately place your crosshair on the following edge of a target in a tracking scenario, so that when the target changes its movement direction, you will get more time on target during the pivot and be able to catch up to it sooner. Edge tracking is the application of a very fundamental principle called underaiming. While you’d never be expected to edge track in a real FPS game, doing it in the trainer does take skill with tension management and smoothness. It also teaches you how to more effectively read movement patterns by changing the position on the target you’re aiming at with respect to its current motion. It’s a high level technique that definitely boosts tracking scores but certainly does not hinder improvement. I consider it to be a necessary part of a good reactive player’s skill set.
Pattern Learning
Another one is pathing in dynamic clicking scenarios and leading your shots to play the timing game. While it is bad to predict and lead your shots all the time, learning the movement patterns and target prioritization in Pasu helps us to build comfort with reading targets in our peripheral vision, which is vital in real games. Pattern learning in general is often criticized by people in the community, but everything within aiming is about recognizing and properly reacting to a pattern. Disregarding that fact leads to a lot of inefficient, brute force aiming.
High FOV
Our last one is running high FOV in target switching scenarios. For example, on PsalmTS, you ideally want to be running 125 FOV for all your runs. Why? Because bad spawn RNG can sometimes have you with no targets on your screen to flick to. In a speed switching scenario, this isn’t really fair, especially when some players can get a lot of center-map spawns. To level the playing field, everyone runs 125 FOV. Does it make the scenario easier to play? Absolutely, but again, it doesn’t circumvent the purpose.
Closing Thoughts
So this is how I think of cheesing and score optimization in aim training. Guys, to be honest, I don’t know why we dig into these topics so hard. At the end of the day, if you’re not a good aimer, playing with a low sensitivity, or a weird FOV, or trying to use some other setting to make the game easier for you is not going to matter.
The real thing that matters in aim training is technique. This is what I focus on when I coach pro players in the Amped program, who do not have the same goals as I do. But even if they focus on their main game while I focus on the trainer, the techniques cross over. It’s all of these ideas like underaiming, tension management, balancing mousepad space, peripheral awareness, having clean flicks, and all of the methods and terms you’re seeing splashed on screen right now that actually matter. And yes, a lot of this tech can lead to higher scores, but that’s not because it’s some secret formula. You’re just learning the best ways to aim when given certain targets that move in certain ways.
So with all that said, I encourage you guys to learn these techniques, to find ways to optimize your training, and hopefully, you’ll get both higher scores and more frags in your main game. I’ll see you guys on stream or in the next video. Happy dot clicking!