marklJs — CS2 Stats
NR76561198000149485[U:1:39883757]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Level 10 among CSDB-tracked players (n=3,007), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.
| Metric | This player | Level 10 median |
|---|---|---|
| Headshot rate | 59.0% | 52.0% |
| Shot accuracy | 14.9% | 13.7% |
| Kill/death ratio | 1.41 | 1.08 |
| Match win rate | 52.2% | 48.8% |
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +50pp win rate · -0.00 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 94% playstyle similarity
Most alike: opening-fight frequency, 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. 66% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
Areas to improve
T-side openings. Opening success drops from 66% on CT to 42% on T — the same duels are being taken with worse setups on the attacking side.
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 (×1.02 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 |
|---|---|---|---|---|---|
| D | 24 | 7–17 | 29% | 0.02 | |
| S | 17 | 12–5 | 71% | 0.06 | |
| B | 15 | 8–7 | 53% | 0.05 | |
| B | 14 | 7–7 | 50% | 0.03 | |
| C | 11 | 4–7 | 36% | 0.03 | |
| A | 7 | 4–3 | 57% | -0.02 | |
| S | 5 | 4–1 | 80% | 0.06 | |
| A | 5 | 3–2 | 60% | 0.01 | |
| golden | — | 1 | 0–1 | 0% | -0.03 |
| — | 1 | 1–0 | 100% | 0.15 |
Across the last 100 tracked matches.
Dust 2 is currently your weakest sufficiently-sampled map (29% over 24). Start with the 6 essential Dust 2 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 resultsWLWLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Dust2 | 153 | 52% | 1.09 | 16.2 |
| Nuke | 96 | 71% | 1.32 | 16.5 |
| Mirage | 78 | 53% | 0.99 | 14.7 |
| Anubis | 45 | 51% | 1.19 | 16.6 |
| Inferno | 33 | 45% | 0.99 | 14.9 |
| Train | 31 | 65% | 1.27 | 18.0 |
| Cache | 8 | 38% | 1.12 | 14.1 |
| Ancient | 3 | 33% | 1.07 | 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.
29% win rate across 24 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 8–13 | -0.03 | 18% | 28 Aug → | ||
| 16–13 | -0.04 | 33% | 17 Aug → | ||
| 13–10 | 0.04 | 26% | 17 Aug → | ||
| 13–9 | 0.05 | 32% | 15 Aug → | ||
| 2–13 | 0.09 | 43% | 15 Aug → | ||
| 13–3 | 0.03 | 21% | 14 Aug → | ||
| 13–4 | 0.07 | 27% | 14 Aug → | ||
| 13–5 | 0.01 | 23% | 7 Aug → | ||
| 13–4 | 0.00 | 17% | 5 Aug → | ||
| 10–13 | 0.02 | 24% | 3 Aug → | ||
| 16–13 | 0.04 | 34% | 1 Aug → | ||
| 9–13 | -0.01 | 40% | 27 Jul → | ||
| 7–13 | 0.01 | 22% | 27 Jul → | ||
| 4–13 | -0.06 | 24% | 27 Jul → | ||
| 13–16 | 0.02 | 42% | 27 Jul → | ||
| 7–13 | -0.03 | 31% | 24 Jul → | ||
| 8–13 | 0.08 | 26% | 13 Jul → | ||
| 13–8 | 0.07 | 30% | 13 Jul → | ||
| 11–13 | 0.07 | 43% | 13 Jul → | ||
| 8–13 | 0.07 | 33% | 13 Jul → | ||
| 13–9 | 0.10 | 33% | 13 Jul → | ||
| 13–7 | 0.10 | 34% | 13 Jul → | ||
| 13–6 | 0.00 | 25% | 12 Jul → | ||
| 10–13 | 0.01 | 31% | 12 Jul → | ||
| 16–13 | 0.07 | 22% | 12 Jul → | ||
| 9–13 | -0.01 | 29% | 12 Jul → | ||
| 10–13 | 0.06 | 28% | 9 Jul → | ||
| 6–13 | 0.07 | 28% | 9 Jul → | ||
| 13–5 | -0.02 | 36% | 9 Jul → | ||
| 13–4 | 0.07 | 27% | 9 Jul → | ||
| 12–12 | 0.06 | 26% | 8 Jul → | ||
| 13–9 | 0.03 | 19% | 4 Jul → | ||
| 7–13 | 0.03 | 33% | 4 Jul → | ||
| 13–11 | 0.02 | 32% | 4 Jul → | ||
| 6–13 | 0.03 | 26% | 4 Jul → | ||
| 13–8 | 0.02 | 21% | 4 Jul → | ||
| 13–11 | 0.08 | 27% | 4 Jul → | ||
| 15–15 | 0.11 | 26% | 2 Jul → | ||
| 13–4 | 0.07 | 31% | 2 Jul → | ||
| 13–10 | 0.08 | 16% | 2 Jul → | ||
| 15–15 | 0.05 | 34% | 2 Jul → | ||
| 13–7 | 0.01 | 23% | 2 Jul → | ||
| 2–13 | 0.04 | 30% | 2 Jul → | ||
| 9–13 | -0.02 | 39% | 2 Jul → | ||
| 13–8 | 0.06 | 26% | 29 Jun → | ||
| 13–9 | 0.05 | 31% | 29 Mar → | ||
| 13–11 | -0.00 | 30% | 25 Mar → | ||
| 13–11 | 0.14 | 30% | 21 Mar → | ||
| 13–6 | 0.11 | 31% | 20 Mar → | ||
| 13–7 | 0.06 | 39% | 20 Mar → | ||
| 13–4 | 0.09 | 32% | 20 Mar → | ||
| 10–13 | 0.04 | 44% | 20 Mar → | ||
| 13–6 | 0.10 | 31% | 20 Mar → | ||
| 11–13 | 0.02 | 30% | 20 Mar → | ||
| 13–6 | -0.05 | 22% | 20 Mar → | ||
| 13–2 | 0.09 | 40% | 20 Mar → | ||
| 13–2 | 0.02 | 38% | 20 Mar → | ||
| 13–10 | 0.14 | 37% | 16 Mar → | ||
| 13–16 | -0.06 | 41% | 13 Mar → | ||
| 10–13 | 0.01 | 22% | 6 Mar → | ||
| 3–13 | 0.02 | 41% | 6 Mar → | ||
| 8–13 | -0.04 | 14% | 28 Feb → | ||
| 13–5 | -0.02 | 26% | 27 Feb → | ||
| 16–19 | -0.01 | 18% | 22 Feb → | ||
| 1–13 | -0.11 | 7% | 15 Feb → | ||
| 13–7 | 0.00 | 21% | 6 Feb → | ||
| 7–13 | -0.01 | 25% | 6 Feb → | ||
| 11–13 | 0.02 | 28% | 6 Feb → | ||
| 13–1 | 0.12 | 27% | 31 Jan → | ||
| 6–13 | 0.05 | 14% | 30 Jan → | ||
| 16–13 | 0.06 | 23% | 30 Jan → | ||
| 10–13 | 0.07 | 32% | 30 Jan → | ||
| 7–13 | 0.01 | 35% | 30 Jan → | ||
| 7–13 | -0.03 | 26% | 25 Jan → | ||
| 9–13 | -0.03 | 12% | 24 Jan → | ||
| 13–9 | 0.02 | 16% | 24 Jan → | ||
| 13–10 | 0.11 | 20% | 24 Jan → | ||
| 2–13 | -0.08 | 16% | 24 Jan → | ||
| 7–13 | -0.01 | 26% | 24 Jan → | ||
| 13–8 | 0.01 | 22% | 24 Jan → | ||
| 13–10 | 0.08 | 26% | 24 Jan → | ||
| 3–13 | -0.04 | 19% | 22 Jan → | ||
| 11–13 | 0.01 | 36% | 22 Jan → | ||
| 13–10 | 0.05 | 28% | 22 Jan → | ||
| 13–5 | 0.03 | 28% | 22 Jan → | ||
| 4–13 | -0.03 | 18% | 22 Jan → | ||
| golden | 8–13 | -0.03 | 14% | 20 Jan → | |
| 5–13 | -0.02 | 21% | 20 Jan → | ||
| 13–8 | 0.04 | 39% | 20 Jan → | ||
| 9–13 | -0.08 | 21% | 19 Jan → | ||
| 13–8 | 0.07 | 50% | 19 Jan → | ||
| 13–2 | 0.15 | 24% | 18 Jan → | ||
| 13–6 | 0.12 | 32% | 18 Jan → | ||
| 7–13 | 0.06 | 27% | 18 Jan → | ||
| 11–13 | -0.04 | 23% | 7 Jan → | ||
| 9–13 | 0.02 | 43% | 28 Dec → | ||
| 13–3 | 0.15 | 51% | 28 Dec → | ||
| 13–5 | 0.12 | 32% | 28 Dec → | ||
| 14–16 | 0.02 | 30% | 19 Aug → | ||
| 15–15 | 0.05 | 26% | 13 Aug → |
Match data via Leetify.
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