shems — CS2 Stats
KR76561198381298908[U:1:421033180]Steam profile ↗✓ No bans
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +50pp win rate · +0.08 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
Sharp aimer
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 donk 96% playstyle similarity
Most alike: opening-duel success, 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 92 — the mechanical foundation is a clear strength.
Areas to improve
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
Reaction time. 578ms 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 (×1.05 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 | 34 | 19–15 | 56% | 0.03 | |
| A | 31 | 19–12 | 61% | 0.05 | |
| C | 21 | 8–13 | 38% | 0.02 | |
| A | 5 | 3–2 | 60% | 0.05 | |
| — | 4 | 1–3 | 25% | 0.03 | |
| — | 2 | 0–2 | 0% | 0.01 | |
| — | 2 | 2–0 | 100% | 0.06 | |
| — | 1 | 1–0 | 100% | 0.10 |
Across the last 100 tracked matches.
Ancient is currently your weakest sufficiently-sampled map (38% over 21). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.
Lifetime stats
Most-used weapons
Lifetime map wins
Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsLWWLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 452 | 53% | 1.15 | 16.8 |
| Dust2 | 279 | 54% | 1.18 | 16.5 |
| Ancient | 199 | 54% | 1.17 | 16.6 |
| Anubis | 138 | 49% | 1.12 | 16.8 |
| Inferno | 100 | 43% | 1.18 | 16.1 |
| Train | 35 | 43% | 1.04 | 15.5 |
| Nuke | 29 | 48% | 0.98 | 15.8 |
| Vertigo | 24 | 58% | 1.35 | 18.4 |
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.
38% win rate across 21 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–3 | 0.12 | 60% | 25 Aug → | ||
| 7–6 | 0.07 | 36% | 23 Aug → | ||
| 13–5 | 0.03 | 29% | 14 Aug → | ||
| 13–10 | 0.10 | 33% | 8 Aug → | ||
| 13–9 | 0.06 | 52% | 8 Aug → | ||
| 11–13 | 0.09 | 27% | 8 Aug → | ||
| 13–9 | 0.13 | 24% | 10 Jun → | ||
| 1–10 | 0.05 | 28% | 10 Jun → | ||
| 13–10 | 0.16 | 32% | 9 Jun → | ||
| 13–8 | 0.13 | 39% | 8 May → | ||
| 6–13 | -0.04 | 15% | 2 May → | ||
| 3–10 | -0.03 | 46% | 7 Apr → | ||
| 5–13 | 0.06 | 52% | 7 Apr → | ||
| 13–5 | -0.01 | 32% | 21 Mar → | ||
| 16–14 | 0.02 | 27% | 15 Mar → | ||
| 11–13 | 0.04 | 38% | 14 Mar → | ||
| 11–13 | 0.01 | 29% | 14 Mar → | ||
| 9–13 | 0.08 | 38% | 13 Mar → | ||
| 13–6 | -0.02 | 8% | 7 Mar → | ||
| 2–13 | 0.00 | 40% | 7 Mar → | ||
| 11–13 | -0.01 | 27% | 7 Mar → | ||
| 7–13 | 0.02 | 25% | 7 Mar → | ||
| 13–11 | 0.01 | 21% | 6 Mar → | ||
| 1–13 | -0.09 | 22% | 6 Mar → | ||
| 13–4 | 0.05 | 24% | 5 Mar → | ||
| 16–12 | 0.06 | 21% | 5 Mar → | ||
| 13–16 | -0.01 | 29% | 5 Mar → | ||
| 11–13 | -0.07 | 33% | 5 Mar → | ||
| 13–7 | -0.01 | 58% | 5 Mar → | ||
| 10–13 | 0.02 | 41% | 3 Mar → | ||
| 13–10 | 0.15 | 36% | 2 Mar → | ||
| 10–2 | 0.05 | 36% | 2 Mar → | ||
| 13–7 | 0.04 | 21% | 28 Feb → | ||
| 3–13 | -0.04 | 26% | 26 Feb → | ||
| 13–11 | 0.00 | 16% | 26 Feb → | ||
| 9–13 | -0.01 | 29% | 23 Feb → | ||
| 13–11 | 0.06 | 28% | 23 Feb → | ||
| 7–13 | 0.02 | 49% | 22 Feb → | ||
| 3–13 | 0.01 | 25% | 22 Feb → | ||
| 13–3 | 0.06 | 27% | 21 Feb → | ||
| 4–7 | 0.05 | 67% | 21 Feb → | ||
| 7–13 | -0.02 | 33% | 20 Feb → | ||
| 9–13 | -0.05 | 31% | 18 Feb → | ||
| 13–3 | 0.09 | 43% | 17 Feb → | ||
| 13–4 | 0.10 | 24% | 16 Feb → | ||
| 13–7 | 0.13 | 24% | 16 Feb → | ||
| 13–2 | 0.14 | 29% | 15 Feb → | ||
| 13–9 | 0.06 | 46% | 15 Feb → | ||
| 11–13 | -0.02 | 45% | 14 Feb → | ||
| 6–13 | 0.09 | 41% | 14 Feb → | ||
| 7–13 | 0.00 | 44% | 12 Feb → | ||
| 13–11 | 0.02 | 22% | 12 Feb → | ||
| 13–9 | 0.05 | 20% | 12 Feb → | ||
| 9–13 | 0.16 | 32% | 12 Feb → | ||
| 2–7 | -0.02 | 100% | 7 Feb → | ||
| 8–13 | -0.02 | 18% | 7 Feb → | ||
| 13–11 | 0.02 | 35% | 7 Feb → | ||
| 13–1 | 0.03 | 26% | 5 Feb → | ||
| 8–13 | 0.04 | 26% | 27 Jan → | ||
| 3–13 | 0.02 | 32% | 27 Jan → | ||
| 6–13 | -0.01 | 29% | 27 Jan → | ||
| 13–7 | 0.10 | 44% | 26 Jan → | ||
| 11–13 | 0.03 | 15% | 26 Jan → | ||
| 11–13 | 0.01 | 33% | 26 Jan → | ||
| 13–6 | 0.09 | 43% | 25 Jan → | ||
| 13–1 | 0.06 | 48% | 25 Jan → | ||
| 13–11 | 0.07 | 36% | 25 Jan → | ||
| 11–13 | 0.09 | 34% | 25 Jan → | ||
| 7–13 | 0.07 | 27% | 25 Jan → | ||
| 13–11 | 0.02 | 32% | 24 Jan → | ||
| 13–9 | 0.10 | 28% | 24 Jan → | ||
| 13–11 | 0.16 | 22% | 22 Jan → | ||
| 13–9 | 0.09 | 17% | 22 Jan → | ||
| 13–4 | 0.04 | 20% | 22 Jan → | ||
| 10–13 | 0.06 | 18% | 17 Jan → | ||
| 0–10 | -0.06 | 50% | 14 Jan → | ||
| 13–10 | 0.03 | 34% | 14 Jan → | ||
| 16–13 | 0.03 | 20% | 13 Jan → | ||
| 13–5 | 0.09 | 26% | 12 Jan → | ||
| 13–10 | 0.01 | 38% | 11 Jan → | ||
| 16–13 | 0.05 | 23% | 10 Jan → | ||
| 3–13 | -0.00 | 41% | 10 Jan → | ||
| 6–13 | -0.02 | 42% | 10 Jan → | ||
| 16–14 | 0.02 | 28% | 8 Jan → | ||
| 13–1 | 0.05 | 46% | 8 Jan → | ||
| 9–2 | 0.25 | 36% | 6 Jan → | ||
| 15–15 | 0.06 | 32% | 4 Jan → | ||
| 8–13 | -0.03 | 40% | 4 Jan → | ||
| 13–1 | 0.12 | 25% | 4 Jan → | ||
| 2–13 | -0.06 | 73% | 4 Jan → | ||
| 10–13 | -0.00 | 20% | 4 Jan → | ||
| 5–13 | -0.09 | 13% | 4 Jan → | ||
| 16–14 | -0.00 | 24% | 3 Jan → | ||
| 13–4 | 0.02 | 33% | 3 Jan → | ||
| 13–10 | -0.00 | 26% | 3 Jan → | ||
| 13–6 | 0.06 | 33% | 3 Jan → | ||
| 13–9 | 0.03 | 25% | 3 Jan → | ||
| 6–13 | 0.01 | 28% | 3 Jan → | ||
| 11–13 | -0.02 | 23% | 3 Jan → | ||
| 11–13 | 0.06 | 24% | 3 Jan → |
Match data via Leetify.