Fix: Godot Client Prediction Drifts From Server

Client predicts player movement, server reconciles. After 5 seconds you’re visibly off the server’s answer. Different tick rate or different physics integrator state.

The Symptom

Snap-back corrections. Player teleports as the server overrides predicted position. Worse at long ping.

The Fix

# project.godot (both client & server)
[physics]
common/physics_ticks_per_second = 60
common/physics_interpolation = false

# GDScript: fixed-step sim in _physics_process
func _physics_process(delta):
    sim_tick += 1
    var input = collect_input(sim_tick)
    apply_input(input)
    var snap = snapshot_state(sim_tick)
    history[sim_tick] = snap

Both ends advance at the same rate. Inputs are tagged with sim_tick. Snapshots in history allow rollback when the server says “at tick N you should have been here.”

Reconciliation

func on_server_correction(server_tick: int, server_state: Dictionary):
    if not history.has(server_tick): return
    restore_state(server_state)
    for t in range(server_tick + 1, sim_tick + 1):
        apply_input(input_history[t])
    # now matches server's authoritative state, plus client inputs

RandomNumberGenerator state belongs in the snapshot too — otherwise re-simulation diverges.

Verifying

Run client + server with intentional 200ms latency. Predicted position matches server reconciliation within 1 unit; corrections are imperceptible.

Understanding the issue

Game physics is a contract between authoring (the body, mass, collision shapes you set) and the solver (how the engine integrates them per tick). Bugs at this boundary usually surface as 'the values look right but the behavior is wrong' - a sign that one side of the contract isn't honoring the other.

The specific bug described above is the kind that surfaces during integration rather than unit testing. It depends on a combination of factors: the asset configuration, the runtime state, the platform's specific behavior. In isolation, each piece looks correct; in combination, the bug emerges. This is why thorough integration testing - playing the actual game in realistic conditions - catches things that automated tests miss.

Why this happens

The triage path for this kind of bug is long. The symptom appears in gameplay, but the cause is in a different system. The reporter describes the gameplay effect; the engineer has to translate that into a hypothesis about the underlying cause. Misdirection is common.

At the engine level, the behavior comes from a deliberate design decision in Godot. The engine team chose a particular trade-off - usually performance versus convenience, or generality versus specificity - and that trade-off has consequences when you push against it. Understanding the trade-off is what turns 'this bug is mysterious' into 'this bug is the expected consequence of this design'.

Verifying the fix

Verifying this fix in isolation is straightforward: reproduce the bug, apply the change, confirm the bug no longer reproduces. The harder verification is regression - did this fix introduce a new bug elsewhere? Run your standard regression suite, plus any tests that exercise the same code path with different inputs.

Reproducibility is the prerequisite for verification. If you can't reliably reproduce the bug pre-fix, you can't reliably verify it post-fix. Spend time getting a clean reproduction before you write any fix code. The fix is fast once you understand the reproduction; the reproduction is the slow part.

Variations to watch for

There's almost always a less obvious case where the same problem applies. The reported case is the one a player hit; the related cases hide because they're rarer or affect fewer players. After fixing the reported case, search the codebase for the pattern - one fix often unlocks several.

Adjacent bugs often share a root cause. After fixing the case you've found, spend an hour searching the codebase for similar patterns. What's the same call with different arguments? The same data flow with a different entity type? The same lifecycle issue in a sibling system? Each match is a candidate for the same fix, or a related fix that prevents future bugs of the same class.

In production

Live games surface this bug class at scale. What's a rare edge case in development becomes a daily occurrence once you have a few thousand concurrent players. The class isn't 'this player has a unique setup'; it's 'one in N thousand sessions will trigger this exact combination'.

When triaging a similar issue in production, prioritize gathering data over hypothesizing causes. A player report describes a symptom; what you need is a build SHA, a session timestamp, and ideally a screen recording or session replay. With those, the bug becomes tractable. Without them, you're guessing at hypothetical reproductions that may not match what the player actually hit.

Performance considerations

Performance implications matter when this bug class scales with player count or asset count. A bug that fires once per session is annoying; a bug that fires once per frame compounds. After fixing, profile the affected code path under realistic load. The fix that's correct for one entity may be too slow for ten thousand.

Diagnostic approach

Diagnosing this class of bug benefits from a structured approach: confirm the symptom, isolate the variables, hypothesize the cause, and verify the hypothesis before writing fix code. Skipping the isolation step is the most common mistake; without it, fixes often address symptoms while the underlying cause continues to produce other variations.

For Godot-specific diagnostics, the editor's profiler is the canonical starting point. Capture a representative frame with the symptom present; compare against a frame without the symptom; the diff often points directly at the cause. If the symptom is non-deterministic, capture multiple frames and look for the pattern - the cause is usually a state transition or a specific input value rather than a continuous effect.

Tooling and ecosystem

The tooling around this bug class matters as much as the fix itself. Good logging, accessible profilers, and clear error messages turn 30-minute investigations into 5-minute ones. If your project doesn't have visibility into this code path, the first fix should add the visibility - the second fix uses it.

Within Godot, the relevant diagnostic surfaces include the standard frame debugger, memory profiler, and engine-specific debug overlays. Each one shows a different facet of what's happening. The frame debugger reveals draw call ordering and state transitions; the memory profiler shows allocation patterns; the debug overlay reveals per-system state. Bugs that resist one tool usually surrender to another - the trick is knowing which tool to reach for first.

Edge cases and pitfalls

Boundary conditions deserve specific testing attention. What happens when the input is zero, maximum, negative, or NaN? What happens at the start of a session vs hours in? What happens at the boundary between two systems handling the same data? These are where bugs hide and where regression tests are most valuable.

When writing a regression test for this fix, focus on the boundary conditions that surfaced the original bug. Tests that exercise the happy path catch obvious regressions; tests that exercise the boundary catch the subtler regressions that look like new bugs but are really the original returning. The latter are the tests that earn their keep over the long life of the project.

Team communication

Document the fix and its rationale in the commit message or attached engineering doc. Future engineers will encounter related issues; the rationale tells them whether your fix is reusable or specific to the case at hand. Without rationale, the fix gets reverted or copied incorrectly.

If this fix touches a system several engineers work in, a short writeup in the team's engineering channel helps. Not a full design doc - a paragraph explaining what was wrong, what's fixed, and what to watch for. Future engineers encountering similar symptoms will search for the fix; making it findable is a small investment that pays back later.

“Same tick rate. Snapshot per step. Rollback on correction.”

Related Issues

For input action just_pressed, see just_pressed. For tween finished signal, see tween signal.

Tick rate locked. Snapshots ready. Sim agrees.