Choose a title
Pick Valorant or CS2 to load the correct sensitivity semantics.
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Félix Lengyel · Streamer / Ex-OWL · Canada
xQc is one of the most-watched Twitch streamers globally and a former Overwatch League pro. His chaotic, high-energy Marvel Rivals streams — often peaking at 100K+ concurrent viewers — were instrumental in the game's viral success at launch.
eDPI
8000
DPI × Sensitivity
DPI
800
Sensitivity
10
Marvel Rivals in-game
Refresh Rate
240 Hz
cm/360°
13.8
Physical wrist movement
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Mouse
Logitech G Pro X Superlight 2
800 DPI
Monitor
BenQ ZOWIE XL2540K
240 Hz · 1920×1080
Dot — Green — 100% OpacityOpen Marvel Rivals → Settings → Gameplay → Crosshair to match this style.
Convert sens 10 (Marvel Rivals) to Valorant, CS2, Apex, Overwatch 2 and more — instantly.
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What sensitivity does xQc use?
xQc plays Marvel Rivals at 10 in-game sensitivity with 800 DPI, giving an eDPI of 8000. In physical terms, this is 13.8 cm per 360° rotation.
What is xQc's eDPI?
xQc's eDPI (Effective DPI) is 8000, calculated as 800 DPI × 10 in-game sensitivity. eDPI lets you compare sensitivities across players regardless of DPI setting.
What mouse does xQc use?
xQc uses the Logitech G Pro X Superlight 2. They play at 800 DPI.
What monitor does xQc use?
xQc uses the BenQ ZOWIE XL2540K running at 240 Hz with a 1920×1080 resolution.
How do I copy xQc's crosshair in Marvel Rivals?
Copy the code above and paste it in CS2 → Settings → Game → Crosshair → Share or Import → Import.
Pro Tip
Filter by game first—Valorant sensitivity does not translate 1:1 to CS2 without cm/360° conversion.
Pick Valorant or CS2 to load the correct sensitivity semantics.
Compare eDPI, resolution, and peripheral choices side by side.
Test adjustments in aim trainers before ranked sessions.
Pro Player Settings Database is structured so you can move from inputs to defensible outputs without hunting for hidden options. Step 1 (“Choose a title”): Pick Valorant or CS2 to load the correct sensitivity semantics. Step 2 (“Browse pros”): Compare eDPI, resolution, and peripheral choices side by side. Step 3 (“Copy responsibly”): Test adjustments in aim trainers before ranked sessions. Following that sequence reduces rounding drift: you lock the scenario first, then layer refinements (tax mode, compounding frequency, activity tier, or niche multiplier) only after baseline numbers look sensible. When you revisit a calculation weeks later, the same order of operations makes spreadsheets and screenshots easier to reconcile with what the UI showed.
Muscle memory rewards narrow eDPI windows; drastic changes destroy flick consistency until retrained.
Hardware parity matters: identical settings on different mice or pads still feel different due to sensor LOD and glide speed.
Revisit Pro Player Settings Database whenever baseline assumptions shift—rates, calendars, population denominators, or hardware targets. The numbers you export today become the audit trail that makes tomorrow’s decision defensible to teammates, clients, or regulators reviewing your methodology.
Competitive FPS performance is a stack of human factors, display timing, and settings you can actually sustain across thousands of repetitions. Crosshair codes encode color, thickness, outlines, and center dot behavior; what reads cleanly on Mirage may wash out on Icebox or Nuke. Sensitivity math reduces to a measurable cm/360°, yet muscle memory still prefers whatever you have rehearsed for seasons. Frame-time and monitor latency tools help you reason about end-to-end click-to-photon delay, but real-world variance from fullscreen optimizations, Reflex, and driver settings will diverge slightly from any single formula. Treat pro settings as structured experiments: change one variable at a time, log outcomes in aim trainers or scrims, and revert when something feels worse under pressure.
Seasoned users pair the in-app insight—“Filter by game first—Valorant sensitivity does not translate 1:1 to CS2 without cm/360° conversion.”—with external checks specific to their industry. For Pro Player Settings Database, treat that guidance as a hypothesis: note the assumption, measure the delta against real-world data you trust, and update defaults when your own history disagrees with generic benchmarks. Documenting those adjustments is what turns a quick answer into a repeatable workflow your team can audit.
Three adjacent tools from the same workflow—open in a new tab mentally, same privacy model here.
We aggregate public interviews and streams; always confirm on live broadcasts because pros experiment often.
Use feedback channels; roster updates depend on public source availability.
It changes visual target size; some players compensate with ADS multipliers—convert using cm/360°, not arbitrary feel.