LangerLuan — CS2 Stats
DE76561198294073148[U:1:333807420]Steam profile ↗✓ No bans
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -20pp win rate · -0.03 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
Sharp aimerExcellent counter-strafing
Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.
Your pro match

Plays most like device 93% playstyle similarity
Most alike: positioning profile, opening-fight frequency.
Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →
Strengths & areas to improve
Strengths
Aim. Aim score of 86 — the mechanical foundation is a clear strength.
Areas to improve
Preaim. Mechanical aim is strong but the crosshair sits 10.6° off target when enemies appear — placement, not flicking, is the bigger win available.
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
Reaction time. 653ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.
Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.
CSDB Rating breakdown
Composite 7.4/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.
Trends
Rolling 5-match average across the last 100 tracked matches, oldest to newest. The delta compares the first third of the window with the last.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
| A | 23 | 13–10 | 57% | 0.03 | |
| C | 18 | 8–10 | 44% | 0.01 | |
| C | 15 | 6–9 | 40% | 0.01 | |
| S | 14 | 10–4 | 71% | 0.02 | |
| B | 13 | 7–6 | 54% | 0.02 | |
| C | 7 | 3–4 | 43% | -0.00 | |
| D | 6 | 1–5 | 17% | -0.02 | |
| — | 4 | 1–3 | 25% | -0.02 |
Across the last 100 tracked matches.
Overpass is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Overpass lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWWWWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 94 | 54% | 1.13 | 16.7 |
| Dust2 | 51 | 59% | 1.03 | 17.3 |
| Inferno | 47 | 55% | 1.35 | 16.3 |
| Ancient | 46 | 39% | 1.12 | 16.8 |
| Nuke | 24 | 46% | 1.35 | 16.9 |
| Anubis | 19 | 68% | 1.11 | 16.4 |
| Train | 13 | 46% | 1.17 | 16.7 |
| Vertigo | 9 | 78% | 1.26 | 17.4 |
Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.
Skill profile
Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.
Recommended for you
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 3–13 | -0.07 | 16% | 30 May → | ||
| 1–13 | -0.01 | 67% | 30 May → | ||
| 12–12 | -0.01 | 44% | 24 May → | ||
| 13–3 | 0.03 | 36% | 24 May → | ||
| 13–8 | 0.02 | 59% | 24 May → | ||
| 13–9 | -0.02 | 30% | 22 May → | ||
| 12–12 | -0.01 | 31% | 22 May → | ||
| 13–3 | -0.00 | 50% | 22 May → | ||
| 7–13 | 0.08 | 27% | 16 May → | ||
| 13–4 | 0.08 | 65% | 16 May → | ||
| 13–5 | 0.06 | 67% | 16 May → | ||
| 13–10 | 0.07 | 28% | 16 May → | ||
| 13–5 | 0.10 | 62% | 16 May → | ||
| 13–7 | 0.04 | 36% | 11 May → | ||
| 13–8 | 0.10 | 30% | 11 May → | ||
| 4–13 | -0.02 | 48% | 11 May → | ||
| 4–13 | 0.01 | 40% | 11 May → | ||
| 13–10 | 0.04 | 48% | 11 May → | ||
| 13–4 | 0.03 | 35% | 11 May → | ||
| 12–12 | -0.01 | 48% | 8 May → | ||
| 12–12 | 0.03 | 33% | 5 May → | ||
| 13–9 | 0.09 | 48% | 5 May → | ||
| 6–13 | 0.05 | 42% | 5 May → | ||
| 8–13 | -0.04 | 16% | 4 May → | ||
| 5–13 | 0.11 | 47% | 1 May → | ||
| 9–13 | 0.00 | 34% | 30 Apr → | ||
| 13–3 | 0.01 | 38% | 19 Apr → | ||
| 13–10 | 0.01 | 25% | 19 Apr → | ||
| 13–7 | 0.08 | 28% | 19 Apr → | ||
| 8–13 | 0.01 | 30% | 19 Apr → | ||
| 6–13 | -0.02 | 37% | 19 Apr → | ||
| 8–13 | -0.03 | 44% | 19 Apr → | ||
| 8–13 | 0.04 | 26% | 18 Apr → | ||
| 13–7 | 0.00 | 32% | 18 Apr → | ||
| 13–7 | 0.02 | 28% | 18 Apr → | ||
| 13–8 | -0.04 | 26% | 18 Apr → | ||
| 13–4 | 0.01 | 29% | 17 Apr → | ||
| 13–6 | 0.08 | 27% | 17 Apr → | ||
| 4–13 | -0.02 | 57% | 16 Apr → | ||
| 13–7 | 0.01 | 42% | 16 Apr → | ||
| 4–13 | 0.09 | 51% | 16 Apr → | ||
| 16–13 | -0.01 | 29% | 15 Apr → | ||
| 11–13 | 0.04 | 37% | 15 Apr → | ||
| 13–8 | 0.03 | 33% | 15 Apr → | ||
| 10–13 | 0.04 | 31% | 15 Apr → | ||
| 6–13 | -0.00 | 32% | 15 Apr → | ||
| 13–7 | 0.07 | 48% | 15 Apr → | ||
| 10–13 | 0.09 | 24% | 15 Apr → | ||
| 10–13 | -0.05 | 15% | 14 Apr → | ||
| 3–13 | 0.00 | 53% | 14 Apr → | ||
| 5–13 | -0.03 | 16% | 14 Apr → | ||
| 7–13 | -0.05 | 34% | 14 Apr → | ||
| 13–0 | 0.09 | 21% | 14 Apr → | ||
| 10–13 | -0.00 | 37% | 14 Apr → | ||
| 7–13 | -0.05 | 44% | 14 Apr → | ||
| 13–9 | -0.00 | 28% | 14 Apr → | ||
| 9–13 | -0.02 | 36% | 14 Apr → | ||
| 13–4 | -0.01 | 35% | 14 Apr → | ||
| 10–13 | 0.05 | 35% | 14 Apr → | ||
| 16–14 | 0.02 | 22% | 14 Apr → | ||
| 13–11 | -0.02 | 42% | 14 Apr → | ||
| 2–13 | 0.01 | 35% | 14 Apr → | ||
| 9–13 | 0.00 | 26% | 14 Apr → | ||
| 13–9 | 0.02 | 33% | 13 Apr → | ||
| 13–11 | -0.05 | 32% | 8 Apr → | ||
| 13–4 | 0.03 | 44% | 8 Apr → | ||
| 13–10 | -0.01 | 44% | 8 Apr → | ||
| 3–13 | -0.01 | 47% | 8 Apr → | ||
| 13–9 | -0.02 | 44% | 8 Apr → | ||
| 15–15 | -0.04 | 26% | 6 Apr → | ||
| 14–16 | 0.10 | 39% | 6 Apr → | ||
| 13–6 | 0.05 | 32% | 6 Apr → | ||
| 11–13 | 0.00 | 42% | 6 Apr → | ||
| 13–7 | 0.04 | 33% | 6 Apr → | ||
| 6–13 | -0.03 | 41% | 5 Apr → | ||
| 11–13 | 0.12 | 38% | 5 Apr → | ||
| 9–13 | 0.02 | 47% | 5 Apr → | ||
| 6–13 | -0.05 | 40% | 5 Apr → | ||
| 8–13 | 0.02 | 60% | 4 Apr → | ||
| 13–7 | 0.06 | 39% | 4 Apr → | ||
| 13–9 | -0.00 | 31% | 3 Apr → | ||
| 16–14 | 0.01 | 20% | 3 Apr → | ||
| 8–13 | 0.01 | 32% | 3 Apr → | ||
| 13–9 | 0.02 | 31% | 2 Apr → | ||
| 5–13 | -0.04 | 57% | 2 Apr → | ||
| 13–3 | 0.04 | 32% | 2 Apr → | ||
| 9–13 | 0.00 | 36% | 1 Apr → | ||
| 13–5 | -0.09 | 19% | 1 Apr → | ||
| 11–13 | -0.04 | 29% | 1 Apr → | ||
| 10–13 | -0.03 | 62% | 1 Apr → | ||
| 13–11 | 0.02 | 39% | 30 Mar → | ||
| 13–7 | 0.08 | 51% | 30 Mar → | ||
| 11–13 | 0.00 | 71% | 30 Mar → | ||
| 13–10 | 0.05 | 35% | 30 Mar → | ||
| 16–14 | -0.04 | 29% | 30 Mar → | ||
| 13–11 | 0.04 | 46% | 29 Mar → | ||
| 9–13 | 0.00 | 35% | 28 Mar → | ||
| 6–13 | -0.03 | 41% | 28 Mar → | ||
| 6–13 | -0.03 | 27% | 28 Mar → | ||
| 13–6 | -0.00 | 28% | 28 Mar → |
Match data via Leetify.