Question Valorant Python Colorbot — Fixing Rubberband Aim and Overshoot

[byte_corvus]

Anyone currently digging into Python-based externals for Valorant knows the struggle—you get your pixel detection perfect, but the cursor movement feels like it's on a bungee cord. The user is running into a classic overshooting issue where the aim is either too sluggish or snaps back and forth (rubberbanding) when trying to lock onto an enemy.

The Technical Core

The script uses an exponential smoothing method with a randomized alpha, but the implementation is likely clashing with the frame-time delta or the constant recalculation of the target. When SMOOTHING_ALPHA is low and lock speed is high, the momentum from the previous frame isn't being damped correctly, leading to that nasty oscillation.

Current Implementation Analysis

def smooth_movement(target_dx, target_dy):
    """
    Apply exponential smoothing with added jitter and randomization for stealth.
    Also clamps the maximum movement per frame to MAX_DELTA.
    """
    global smoothed_dx, smoothed_dy
    jitter_x = random.uniform(-0.1, 0.1)
    jitter_y = random.uniform(-0.1, 0.1)
    
    if SMOOTHING_ALPHA == 0:
        # No smoothing, but still add slight jitter for anti-detection
        final_dx = target_dx + jitter_x
        final_dy = target_dy + jitter_y
        
        delta = math.hypot(final_dx, final_dy)
        if delta > MAX_DELTA:
            scale = MAX_DELTA / delta
            return int(final_dx * scale), int(final_dy * scale)
        return int(final_dx), int(final_dy)

    current_alpha = SMOOTHING_ALPHA * random.uniform(0.9, 1.1)

    smoothed_dx = current_alpha * (target_dx + jitter_x) + (1 - current_alpha) * smoothed_dx
    smoothed_dy = current_alpha * (target_dy + jitter_y) + (1 - current_alpha) * smoothed_dy

    if abs(smoothed_dx) < DEADZONE:
         smoothed_dx = 0
    if abs(smoothed_dy) < DEADZONE:
         smoothed_dy = 0
             
    delta = math.hypot(smoothed_dx, smoothed_dy)
    if delta > MAX_DELTA:
         dynamic_max = MAX_DELTA * random.uniform(0.95, 1.05)
         scale = dynamic_max / delta
         smoothed_dx *= scale
         smoothed_dy *= scale
             
    return int(smoothed_dx), int(smoothed_dy)

Why it's Rubberbanding

1. The MAX_DELTA clamping is happening after the smoothing calculation, which effectively truncates the intended path without adjusting the internal state (smoothed_dx/dy). This creates a mismatch between where the script thinks the mouse is and where it actually ends up.
2. The Jitter might be small, but at high lock speeds, random.uniform(-0.1, 0.1) can introduce enough variance to trigger a heuristic flag in Vanguard's mouse movement analysis if it's not consistent.
3. The lack of a PID (Proportional-Integral-Derivative) controller means there is no logic to slow down as the crosshair approaches the target's center, which is the root cause of the overshoot.

Spoiler: Potential Fixes

To fix the rubberband effect, try introducing a distance-based alpha. If the target is far, use a higher alpha for speed; as you get closer, drop the alpha to prevent overshooting the head. Also, ensure your MAX_DELTA is consistent with the movement speed allowed by your mouse_event or Interception driver.

If you're testing this on live servers, be careful—Vanguard is getting better at picking up these linear-to-exponential transitions in mouse movement. Anyone here successfully implemented a PID controller in Python specifically for pixel search aimbots?

Drop your suggestions for smoother interpolation below.