Understanding Network Latency in Multiplayer Games
Network latency is the enemy of responsive gameplay. When a player presses a button, that input doesn’t instantly reach the server—it travels across physical cables and through routers, typically taking anywhere from 20 to 200 milliseconds depending on distance and connection quality. For fast-paced games, that delay feels like an eternity.
The real challenge isn’t just accepting latency exists—it’s making players forget about it. Players expect their character to respond immediately when they act. If there’s a noticeable delay between their input and what happens on screen, the game feels broken, laggy, unresponsive. You’ve got to make it invisible.
Typical Latency Ranges
- Local network (LAN): 1-5ms
- Same country: 20-50ms
- International: 100-150ms
- Satellite connections: 400-600ms
Players in Australia connecting to European servers might experience 200ms+ latency. That’s a fifth of a second. In competitive games, that’s brutal. But it’s still playable if you handle it correctly.
Client-Side Prediction: Making Input Instant
Here’s the trick that makes modern multiplayer games feel responsive: don’t wait for the server. When the player moves, update their character position immediately on their own client. Show movement right away. Then send that input to the server. When the server responds, either confirm the movement was valid or correct it if something went wrong.
This is called client-side prediction, and it’s essential. Without it, every action feels delayed. With it, your own character feels snappy and responsive, even on high-latency connections.
The catch? You’re guessing. You’re predicting what the server will say is valid before the server actually responds. Sometimes you’ll predict wrong—maybe another player was in the way, or the server disagreed with your position. When that happens, you need to smoothly correct your position without jarring the player.
Interpolation and Extrapolation: Smooth Movement
Your character isn’t the only one moving. Other players are moving too. But you’re not getting real-time updates about where they are—you’re getting updates every 66 to 100 milliseconds (that’s 10-15 updates per second for most games). That’s not enough to create smooth motion if you just snap their position to each new update.
So you interpolate. Between updates, you smoothly move the other player from their last known position toward the next known position. It’s like drawing the in-between frames in an animation. The server says “player was at position X, now they’re at position Y”—and you draw all the motion in between.
But interpolation only shows where players were. Extrapolation tries to predict where they’re going. If a player’s been moving north at 5 meters per second, extrapolation says they’ll probably still be moving north. It extends their movement curve forward. This works great until they stop suddenly or change direction—then you’ve predicted wrong, and you need to correct smoothly.
Most games use a blend: recent history is interpolated (we know they were definitely there), and the very immediate future is extrapolated (we’re guessing where they’re heading). It’s elegant and it works.
Authority and State Reconciliation
Here’s where it gets tricky. You’re predicting client-side, other players are predicting their movements, but only the server knows what’s actually true. The server is the authority. It’s the source of truth.
When your prediction differs from the server’s reality—which it will, eventually—you need to reconcile. You need to correct your local state to match what the server says is real. But you can’t just snap. If you snap the player to the correct position, it looks like a glitch. You need to smoothly transition.
The best approach? Keep a small buffer of recent inputs. When the server responds with a correction, replay your inputs forward from that corrected state. This is called input buffering and replay. It keeps things smooth and maintains the illusion that you had perfect control all along.
Network Tick Rates and Update Frequency
How often does the server broadcast state updates? Every 10 milliseconds? Every 100 milliseconds? This matters hugely. Higher tick rates mean more frequent updates, smoother motion, less room for error. But they also mean more bandwidth and more server CPU.
Most competitive shooters run at 64 or 128 ticks per second (every 7.8 or 15.6ms). Fighting games sometimes go even higher. Battle royales often run at 20-30 ticks to save bandwidth. The trade-off is clear: more frequent updates = smoother, more responsive gameplay = higher costs.
Noticeable jitter in motion, requires heavy extrapolation
Good balance for most games, smooth interpolation
Very smooth, minimal extrapolation needed, high bandwidth
You also need to account for jitter—variance in latency. Sometimes a packet arrives in 50ms, sometimes 80ms. A buffer helps smooth this out. Instead of rendering updates the instant they arrive, you hold them briefly and render them slightly in the past. This sounds backwards, but it means you’re almost always interpolating between two known states instead of extrapolating into the unknown.
Lag Compensation and Hit Detection
In competitive games, lag compensation is critical. When a player shoots at another player, that input travels to the server with latency. By the time the server processes it, the target has moved. Without compensation, hits would feel inconsistent and unfair.
The solution: the server rewinds. It looks at where the target player was at the time the shooter sent their input, not where they are now. It’s like the server says “Let me check if you would’ve hit if latency didn’t exist.” This is controversial—players on high latency get an advantage—but it feels fair to the person shooting.
Some games use a hybrid approach. They compensate partially, or they only compensate within reasonable latency ranges. The goal is always the same: make it feel like latency doesn’t exist, at least from the perspective of the player performing the action.
Practical Implementation Considerations
Building this stuff isn’t trivial. You’re managing multiple versions of game state simultaneously. On the client, you’ve got the predicted state, the interpolated state, and the server-confirmed state. They need to stay loosely in sync without conflicting.
Most game engines have networking libraries that handle some of this automatically. Unreal’s Replication Graph, Unity’s Netcode, custom solutions like Mirror—they all tackle similar problems. But understanding the principles underneath helps you know when things aren’t working right and how to debug them.
Testing on real latency is essential. Don’t just test on localhost. Simulate real network conditions. Tools like NetLimiter or tc (traffic control) on Linux let you add latency and jitter to your connection. See how your game feels at 50ms, 100ms, 150ms. You’ll quickly discover which techniques work and which ones create motion that feels wrong.
One more thing: always account for the worst case. If your game needs to handle 200ms latency, test it. Your extrapolation and prediction algorithms need to gracefully degrade. They shouldn’t break or look horrible at high latency—they should just be less perfect, which is fine.
Bringing It All Together
Managing latency isn’t about eliminating it. It’s about hiding it. You can’t control the physics of network travel, but you can control how the game presents itself to players. With client-side prediction, interpolation, extrapolation, proper tick rates, and lag compensation, you create the illusion of instant response even when reality says otherwise.
The best networked games feel immediate and responsive. Players don’t think about latency because it’s been engineered away at every level. That’s the goal. That’s what separates a game that feels good from one that feels frustrating, no matter how powerful the servers are or how fast the internet is.
