CHINESE MODE — CS2 Stats
76561198856107629[U:1:895841901]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Level 5 among CSDB-tracked players (n=918), 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 5 median | Level 6 median | vs Level 6 |
|---|---|---|---|---|
| Headshot rate | 39.2% | 44.2% | 44.9% | 5.7% short |
| Shot accuracy | 16.4% | 11.2% | 11.8% | above |
| Kill/death ratio | 1.10 | 1.04 | 1.04 | above |
| Match win rate | 46.7% | 45.3% | 45.3% | above |
This profile matches the typical Level 6 player on 3 of 4 comparable metrics.
Widest gap: Headshot rate. That is the metric furthest from the Level 6 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +0pp win rate · +0.01 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 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 90 — 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.
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 7.2/10 (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 | 15–12 | 56% | 0.01 | |
| B | 17 | 8–9 | 47% | 0.01 | |
| D | 16 | 5–11 | 31% | -0.01 | |
| B | 15 | 8–7 | 53% | 0.00 | |
| B | 11 | 5–6 | 45% | -0.00 | |
| D | 8 | 1–7 | 13% | 0.01 | |
| — | 4 | 2–2 | 50% | 0.03 | |
| — | 2 | 0–2 | 0% | -0.05 |
Across the last 100 tracked matches.
Vertigo is currently your weakest sufficiently-sampled map (13% over 8). Start with the 6 essential Vertigo 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 resultsWWWWW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Nuke | 1 | 100% | 1.07 | 16.0 |
| Mirage | 1 | 100% | 0.33 | 5.0 |
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.
13% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 6–13 | 0.03 | 42% | 28 Aug → | ||
| 4–13 | 0.03 | 29% | 28 Aug → | ||
| 13–6 | 0.07 | 19% | 28 Aug → | ||
| 8–13 | 0.04 | 16% | 28 Aug → | ||
| 16–13 | 0.07 | 13% | 27 Aug → | ||
| 13–7 | 0.03 | 18% | 27 Aug → | ||
| 13–10 | 0.01 | 16% | 27 Aug → | ||
| 4–13 | -0.01 | 11% | 27 Aug → | ||
| 8–13 | 0.01 | 45% | 24 Aug → | ||
| 16–12 | 0.08 | 7% | 24 Aug → | ||
| 7–13 | 0.00 | 22% | 24 Aug → | ||
| 8–13 | -0.00 | 27% | 23 Aug → | ||
| 13–3 | 0.06 | 20% | 23 Aug → | ||
| 13–7 | 0.06 | 24% | 23 Aug → | ||
| 13–4 | 0.03 | 15% | 18 Aug → | ||
| 14–16 | 0.01 | 39% | 5 Aug → | ||
| 13–6 | 0.05 | 16% | 5 Aug → | ||
| 6–13 | -0.01 | 5% | 4 Aug → | ||
| 5–13 | 0.03 | 18% | 3 Aug → | ||
| 7–1 | 0.02 | 11% | 30 Jul → | ||
| 13–11 | 0.02 | 16% | 29 Jul → | ||
| 13–6 | 0.05 | 28% | 29 Jul → | ||
| 6–13 | -0.01 | 21% | 28 Jul → | ||
| 9–13 | 0.00 | 23% | 28 Jul → | ||
| 12–12 | 0.01 | 33% | 28 Jul → | ||
| 2–13 | -0.07 | 75% | 28 Jul → | ||
| 5–13 | 0.02 | 38% | 28 Jul → | ||
| 2–13 | -0.06 | 25% | 27 Jul → | ||
| 13–5 | 0.01 | 36% | 27 Jul → | ||
| 13–7 | 0.07 | 34% | 26 Jul → | ||
| 5–13 | -0.02 | 19% | 26 Jul → | ||
| 4–13 | -0.03 | 33% | 24 Jul → | ||
| 5–13 | 0.00 | 38% | 23 Jul → | ||
| 13–7 | 0.01 | 10% | 23 Jul → | ||
| 4–9 | -0.07 | 31% | 20 Jul → | ||
| 0–13 | -0.10 | 20% | 19 Jul → | ||
| 13–9 | -0.07 | 4% | 19 Jul → | ||
| 6–13 | 0.01 | 41% | 16 Jul → | ||
| 13–2 | -0.06 | 14% | 15 Jul → | ||
| 13–10 | -0.06 | 15% | 15 Jul → | ||
| 15–15 | -0.05 | 19% | 15 Jul → | ||
| 13–8 | 0.02 | 15% | 14 Jul → | ||
| 10–13 | -0.02 | 17% | 14 Jul → | ||
| 7–13 | 0.04 | 12% | 14 Jul → | ||
| 13–9 | 0.03 | 24% | 14 May → | ||
| 2–13 | -0.09 | 29% | 8 May → | ||
| 10–13 | -0.09 | 22% | 7 May → | ||
| 13–8 | 0.01 | 36% | 5 May → | ||
| 13–5 | 0.04 | 37% | 5 May → | ||
| 11–13 | -0.03 | 19% | 4 May → | ||
| 11–13 | -0.04 | 29% | 4 May → | ||
| 12–12 | 0.00 | 24% | 4 May → | ||
| 7–13 | -0.05 | 26% | 3 May → | ||
| 11–13 | 0.04 | 21% | 3 May → | ||
| 13–9 | 0.08 | 11% | 30 Apr → | ||
| 13–8 | 0.07 | 18% | 29 Apr → | ||
| 11–13 | 0.04 | 28% | 29 Apr → | ||
| 7–13 | 0.03 | 30% | 29 Apr → | ||
| 13–3 | 0.09 | 26% | 29 Apr → | ||
| 12–12 | 0.05 | 52% | 28 Apr → | ||
| 13–11 | -0.01 | 38% | 28 Apr → | ||
| 13–9 | -0.02 | 22% | 28 Apr → | ||
| 13–6 | 0.01 | 58% | 28 Apr → | ||
| 10–13 | 0.02 | 16% | 26 Apr → | ||
| 8–13 | -0.01 | 14% | 26 Apr → | ||
| 11–13 | -0.04 | 17% | 26 Apr → | ||
| 13–11 | 0.01 | 14% | 26 Apr → | ||
| 15–15 | -0.02 | 20% | 26 Apr → | ||
| 8–13 | 0.01 | 41% | 26 Apr → | ||
| 10–1 | -0.02 | 67% | 26 Apr → | ||
| 13–7 | -0.03 | 16% | 23 Apr → | ||
| 13–10 | -0.05 | 29% | 23 Apr → | ||
| 10–13 | -0.05 | 10% | 22 Apr → | ||
| 6–13 | -0.09 | 0% | 22 Apr → | ||
| 11–13 | -0.03 | 18% | 22 Apr → | ||
| 13–2 | -0.02 | 19% | 22 Apr → | ||
| 7–13 | 0.04 | 16% | 21 Apr → | ||
| 13–4 | -0.01 | 18% | 21 Apr → | ||
| 11–13 | 0.01 | 11% | 13 Apr → | ||
| 13–4 | 0.03 | 14% | 13 Apr → | ||
| 7–13 | 0.06 | 33% | 10 Apr → | ||
| 13–7 | 0.10 | 8% | 10 Apr → | ||
| 9–13 | -0.01 | 19% | 7 Apr → | ||
| 13–10 | 0.03 | 22% | 7 Apr → | ||
| 9–13 | -0.03 | 11% | 7 Apr → | ||
| 5–13 | -0.04 | 16% | 6 Apr → | ||
| 12–3 | -0.00 | 22% | 4 Apr → | ||
| 4–12 | -0.06 | 25% | 4 Apr → | ||
| 0–13 | -0.04 | 45% | 4 Apr → | ||
| 4–13 | -0.00 | 28% | 3 Apr → | ||
| 13–8 | 0.00 | 20% | 1 Apr → | ||
| 13–1 | -0.01 | 8% | 1 Apr → | ||
| 13–7 | 0.13 | 14% | 31 Mar → | ||
| 10–13 | -0.02 | 12% | 31 Mar → | ||
| 13–11 | -0.03 | 14% | 30 Mar → | ||
| 6–13 | -0.06 | 24% | 30 Mar → | ||
| 1–13 | 0.01 | 47% | 27 Mar → | ||
| 13–8 | 0.06 | 31% | 27 Mar → | ||
| 15–15 | 0.02 | 18% | 26 Mar → | ||
| 13–6 | -0.01 | 21% | 26 Mar → |
Match data via Leetify.
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