wxlff_ — CS2 Stats
76561198452594401[U:1:492328673]
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +20pp win rate · +0.01 avg rating
Player DNA
Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.
Sharp aimerStrong CT-side opener
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 s1mple 91% playstyle similarity
Most alike: opening-fight frequency, opening-duel success.
Where you differ: lower utility contribution.
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 89 — the mechanical foundation is a clear strength.
CT openings. 68% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
Areas to improve
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
T-side openings. Opening success drops from 68% on CT to 43% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 587ms 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 7.5/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.02 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 | 27 | 16–11 | 59% | 0.03 | |
| A | 16 | 9–7 | 56% | 0.03 | |
| B | 11 | 5–6 | 45% | 0.01 | |
| C | 10 | 4–6 | 40% | 0.02 | |
| B | 8 | 4–4 | 50% | 0.00 | |
| A | 7 | 4–3 | 57% | 0.03 | |
| D | 6 | 2–4 | 33% | 0.00 | |
| — | 4 | 3–1 | 75% | 0.02 | |
| — | 4 | 1–3 | 25% | 0.00 | |
| warden | — | 2 | 0–2 | 0% | 0.10 |
| shelter | — | 1 | 0–1 | 0% | -0.06 |
| fachwerk | — | 1 | 0–1 | 0% | 0.05 |
| boulder | — | 1 | 1–0 | 100% | 0.02 |
| alpine | — | 1 | 0–1 | 0% | 0.07 |
| stronghold | — | 1 | 0–1 | 0% | -0.02 |
Across the last 100 tracked matches.
Mirage is currently your weakest sufficiently-sampled map (33% over 6). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWWLWW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Ancient | 436 | 54% | 1.14 | 16.3 |
| Dust2 | 428 | 58% | 1.28 | 17.5 |
| Anubis | 256 | 50% | 1.06 | 15.4 |
| Mirage | 208 | 46% | 1.07 | 14.7 |
| Inferno | 122 | 47% | 1.07 | 15.0 |
| Overpass | 77 | 52% | 1.09 | 15.3 |
| Train | 50 | 28% | 1.05 | 15.3 |
| Nuke | 36 | 36% | 0.94 | 14.3 |
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.
33% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 16–13 | 0.02 | 27% | 22 Aug → | ||
| 13–6 | 0.03 | 39% | 20 Aug → | ||
| 13–10 | 0.05 | 28% | 15 Aug → | ||
| 13–3 | 0.02 | 48% | 14 Aug → | ||
| 12–12 | 0.04 | 36% | 14 Aug → | ||
| 13–9 | 0.01 | 17% | 10 Aug → | ||
| 13–9 | 0.05 | 27% | 9 Aug → | ||
| 13–4 | 0.03 | 31% | 9 Aug → | ||
| 2–13 | -0.01 | 27% | 8 Aug → | ||
| 12–12 | 0.02 | 31% | 8 Aug → | ||
| shelter | 2–13 | -0.06 | 38% | 25 Jul → | |
| fachwerk | 5–13 | 0.05 | 42% | 25 Jul → | |
| boulder | 13–5 | 0.02 | 36% | 25 Jul → | |
| 13–9 | 0.10 | 11% | 13 Jul → | ||
| 13–10 | 0.05 | 19% | 12 Jul → | ||
| 10–13 | -0.03 | 17% | 11 Jul → | ||
| 13–10 | 0.01 | 52% | 3 Jul → | ||
| 13–5 | 0.03 | 44% | 27 Jun → | ||
| 12–12 | -0.01 | 30% | 19 Jun → | ||
| 8–13 | 0.03 | 14% | 12 Jun → | ||
| 8–13 | 0.01 | 36% | 5 Jun → | ||
| 11–1 | 0.07 | 24% | 5 Jun → | ||
| 2–13 | -0.06 | 11% | 1 Jun → | ||
| 13–9 | -0.02 | 22% | 29 May → | ||
| 0–13 | -0.08 | 18% | 29 May → | ||
| 9–13 | 0.00 | 23% | 15 May → | ||
| 12–12 | 0.06 | 23% | 15 May → | ||
| 13–7 | 0.09 | 20% | 9 May → | ||
| 13–9 | 0.02 | 36% | 9 May → | ||
| 13–5 | 0.01 | 32% | 8 May → | ||
| 12–12 | -0.01 | 32% | 8 May → | ||
| 11–1 | 0.07 | 34% | 8 May → | ||
| 12–12 | -0.02 | 29% | 5 May → | ||
| 13–7 | 0.13 | 26% | 4 May → | ||
| 13–8 | 0.05 | 25% | 4 May → | ||
| 13–8 | 0.07 | 26% | 4 May → | ||
| 13–8 | 0.03 | 35% | 1 May → | ||
| 2–13 | -0.03 | 3% | 27 Apr → | ||
| 13–10 | -0.06 | 40% | 23 Apr → | ||
| 6–13 | 0.02 | 50% | 23 Apr → | ||
| 13–6 | 0.01 | 10% | 22 Apr → | ||
| warden | 7–13 | 0.22 | 50% | 19 Apr → | |
| 13–9 | -0.01 | 21% | 18 Apr → | ||
| 5–13 | -0.07 | 20% | 17 Apr → | ||
| 13–6 | -0.01 | 30% | 17 Apr → | ||
| 13–11 | 0.06 | 24% | 14 Apr → | ||
| 13–6 | 0.17 | 36% | 11 Apr → | ||
| 13–9 | -0.00 | 39% | 5 Apr → | ||
| 1–13 | -0.02 | 44% | 5 Apr → | ||
| 13–11 | -0.03 | 13% | 2 Apr → | ||
| 12–12 | 0.05 | 16% | 2 Apr → | ||
| 8–13 | -0.06 | 18% | 2 Apr → | ||
| 5–13 | -0.06 | 25% | 1 Apr → | ||
| 13–9 | 0.12 | 41% | 28 Mar → | ||
| 13–11 | 0.09 | 33% | 18 Mar → | ||
| 12–12 | 0.11 | 20% | 18 Mar → | ||
| 9–1 | -0.03 | 22% | 18 Mar → | ||
| 13–5 | 0.05 | 31% | 16 Mar → | ||
| 1–13 | -0.10 | 14% | 16 Mar → | ||
| 10–13 | 0.03 | 29% | 16 Mar → | ||
| 12–12 | 0.05 | 34% | 16 Mar → | ||
| 13–8 | -0.01 | 34% | 10 Mar → | ||
| 6–13 | 0.03 | 23% | 3 Mar → | ||
| 6–13 | 0.02 | 28% | 3 Mar → | ||
| 12–12 | 0.01 | 35% | 28 Feb → | ||
| 13–9 | 0.11 | 27% | 28 Feb → | ||
| alpine | 6–13 | 0.07 | 53% | 27 Feb → | |
| 13–8 | 0.11 | 20% | 27 Feb → | ||
| 13–10 | -0.01 | 12% | 27 Feb → | ||
| 13–3 | 0.08 | 29% | 24 Feb → | ||
| 16–12 | 0.07 | 33% | 24 Feb → | ||
| stronghold | 5–13 | -0.02 | 20% | 20 Feb → | |
| 5–13 | -0.07 | 16% | 20 Feb → | ||
| 13–11 | 0.15 | 23% | 20 Feb → | ||
| 11–13 | 0.03 | 33% | 18 Feb → | ||
| 6–13 | -0.06 | 23% | 17 Feb → | ||
| 9–13 | 0.02 | 30% | 11 Feb → | ||
| 8–13 | -0.05 | 23% | 10 Feb → | ||
| 7–13 | -0.06 | 10% | 10 Feb → | ||
| 13–7 | 0.11 | 32% | 10 Feb → | ||
| 9–13 | 0.00 | 20% | 7 Feb → | ||
| 9–13 | 0.01 | 21% | 6 Feb → | ||
| warden | 11–13 | -0.01 | 20% | 6 Feb → | |
| 4–13 | -0.10 | 16% | 6 Feb → | ||
| 22–20 | 0.03 | 23% | 4 Feb → | ||
| 8–13 | 0.01 | 25% | 2 Feb → | ||
| 13–6 | 0.06 | 19% | 30 Jan → | ||
| 16–13 | 0.05 | 16% | 30 Jan → | ||
| 10–13 | 0.06 | 26% | 27 Jan → | ||
| 2–13 | -0.04 | 38% | 27 Jan → | ||
| 13–10 | 0.02 | 24% | 25 Jan → | ||
| 13–8 | 0.08 | 19% | 25 Jan → | ||
| 13–8 | 0.03 | 37% | 23 Jan → | ||
| 16–13 | -0.01 | 28% | 22 Jan → | ||
| 4–13 | 0.06 | 44% | 21 Jan → | ||
| 10–13 | -0.03 | 42% | 17 Jan → | ||
| 12–12 | 0.01 | 19% | 17 Jan → | ||
| 6–13 | -0.05 | 9% | 17 Jan → | ||
| 7–13 | 0.01 | 21% | 7 Jan → | ||
| 3–13 | 0.10 | 26% | 7 Jan → |
Match data via Leetify.