Please Click Here for more information on our used items. Please note this is a used item and comes with a 30 day warranty. A range limiter offers added security.įrame Description - 11-gauge steel frame ensures maximum structural integrity Each frame receives an electrostatic powder coat finish to ensure maximum adhesion and durabilityĭimensions (L x W x H) - 84 in x 61 in x 54 in (213 cm x 155 cm x 137 cm) Easy flip in and out racking handles allow the user to set a desired start/stop position. Linear bearings on guide rods provide an extremely smooth motion. The Linear Hack Squat was specifically designed to train a movement that other machines weren’t focusing on. Large footplate accomodates various user sizes Wear resistant roller mechanism for an exceptionally smooth and quiet motion This may include surface rust and scratches, but these imperfections are purely cosmetic, demonstrated in the provided photos, and have absolutley no impact on the functionality of the product.ĭesigned to accommodate various users with a linear press training motion. A very rare piece to find on the used market, be quick, as we only have one available.Īll our used gym equipment is sourced from a commercial or private members-only clubs, and thus will have signs of usage as would be expected in this environment. This item has been well looked after, which is evident in the items condition. cpp.We have recently sourced this fantastic Linear Hack Squat, manufactured by Hammer Strength, from a commercial gym where it was used from new for a few years under a service contract. Just change the function at the top (needs to be in c++ math), run it and copy the output LUT into rawaccell. If you want to make a graph from a custom function you can use this trash program that i used to create some points for the LUT. But this LUT mode of rawaccell allows to fully customize the graph for the game or scenario you are playing or the weaknesses of your aim. Its probably needed to find a function or graph with the right amount and for example to only apply the reverse acceleration at the speeds you use for tracking and not at flicking speeds. I really didnt test it much yet but because someone asked: Reverse acceleration like √x should increase the smoothness but make the flicks / adjusts worse because you have to move your mouse even faster for flicks and the shakiness at the end of a flick will be amplified. Maybe someone else can figure out a good custom / reverse accell graph for overall aim or has already tried this? Theoretically, reverse accell could help on any tracking scenario when smoothness is the problem but i dont play other scenarios like smoothbot, pgti and controlsphere so i dont have scores to compare when trying out graphs. I also tried the √x function and it improved my horizontal precision tracking scores a little but it feels really weird overall. But this graph only works for the movement speed of this scenario. It feels like aim assist (target seems bigger) and with it my problem is only the adjustment on target and not the smooth track anymore. The graph allows to use a higher range of mouse speeds for the speeds that are needed to stay on target and it has an increase in speed for the faster readjustments. My usual pb on the same setup was 12k before. Just for trying out the possibilities, i tried to make a graph for midrange long strafes thin invincible and got a 15.6k score (would be #2 on leaderboard, maybe #1 if i warmed up), first try with new settings, ofc with submitting to leaderboards disabled.
Maybe this can be good to get better overall aim for people who have good static / flicking and bad tracking but it can also be used to cheese scores. Now i found out that rawaccell added a mode called LUT where you can enter custom graphs and use reverse accell. It was only possible to not apply the acceleration at tracking speeds. Graphs that have the opposite effect were not really possible to do in rawaccell before as far as i know. Normal acceleration that could be done with rawaccell is known to help flicks but when applied at low speeds it makes smooth tracking harder because it increases the difference between the speed of the mouse and speed of the target.