gucci — CS2 Stats
76561197964100034[U:1:3834306]
How this compares with the same rank
Median values for Level 2 among CSDB-tracked players (n=338), 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 2 median | vs Level 2 |
|---|---|---|---|
| Headshot rate | 38.3% | 42.1% | 3.9% short |
| Shot accuracy | 13.0% | 12.9% | meets |
| Kill/death ratio | 1.09 | 1.00 | above |
| Match win rate | 47.6% | 42.9% | above |
This profile matches the typical Level 2 player on 3 of 4 comparable metrics.
Widest gap: Headshot rate. That is the metric furthest from the Level 2 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: +20pp win rate · +0.01 avg rating
Player DNA
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 NiKo 83% playstyle similarity
Most alike: utility contribution, opening-fight frequency.
Where you differ: lower opening-duel success; lower aim profile.
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
Areas to improve
CT openings. Opening success drops from 38% on T to 22% on CT — first contacts on the defending side are being lost.
Reaction time. 612ms 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 4.8/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 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 |
|---|---|---|---|---|---|
| C | 36 | 16–20 | 44% | -0.02 | |
| B | 22 | 11–11 | 50% | -0.02 | |
| S | 17 | 12–5 | 71% | -0.00 | |
| B | 12 | 6–6 | 50% | -0.02 | |
| S | 6 | 4–2 | 67% | -0.00 | |
| D | 5 | 1–4 | 20% | 0.00 | |
| — | 2 | 0–2 | 0% | -0.02 |
Across the last 100 tracked matches.
Nuke is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Nuke 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 resultsLLLWL
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
Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.
- Best CS2 CrosshairAim Training →
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 11.564% — below the 15% mark we flag
- Advanced Mechanics
You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.
T opening duels 37.885% — below the 40% mark we flag
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–3 | 0.08 | 19% | 29 Aug → | ||
| 11–13 | -0.05 | 7% | 29 Aug → | ||
| 13–9 | -0.03 | 12% | 29 Aug → | ||
| 13–7 | -0.04 | 11% | 29 Aug → | ||
| 5–13 | 0.02 | 15% | 29 Aug → | ||
| 7–13 | 0.01 | 9% | 28 Aug → | ||
| 9–13 | -0.03 | 8% | 28 Aug → | ||
| 13–8 | -0.01 | 18% | 28 Aug → | ||
| 8–13 | -0.00 | 17% | 28 Aug → | ||
| 13–8 | -0.05 | 11% | 27 Aug → | ||
| 11–13 | -0.03 | 10% | 26 Aug → | ||
| 7–13 | -0.04 | 10% | 26 Aug → | ||
| 13–8 | 0.03 | 11% | 26 Aug → | ||
| 10–13 | -0.09 | 5% | 25 Aug → | ||
| 16–13 | -0.01 | 11% | 25 Aug → | ||
| 15–15 | -0.03 | 10% | 24 Aug → | ||
| 9–13 | 0.02 | 17% | 24 Aug → | ||
| 15–15 | -0.04 | 8% | 24 Aug → | ||
| 8–13 | 0.01 | 15% | 23 Aug → | ||
| 13–8 | -0.06 | 0% | 23 Aug → | ||
| 13–8 | 0.01 | 16% | 23 Aug → | ||
| 9–13 | -0.01 | 4% | 21 Aug → | ||
| 13–6 | 0.06 | 16% | 21 Aug → | ||
| 10–13 | -0.05 | 16% | 21 Aug → | ||
| 13–8 | 0.03 | 10% | 21 Aug → | ||
| 13–3 | 0.04 | 18% | 20 Aug → | ||
| 13–3 | 0.00 | 16% | 20 Aug → | ||
| 13–4 | -0.01 | 11% | 20 Aug → | ||
| 13–8 | -0.03 | 13% | 20 Aug → | ||
| 4–13 | -0.07 | 11% | 20 Aug → | ||
| 13–9 | 0.03 | 7% | 19 Aug → | ||
| 7–13 | -0.06 | 8% | 19 Aug → | ||
| 5–13 | -0.06 | 17% | 19 Aug → | ||
| 13–8 | 0.03 | 13% | 18 Aug → | ||
| 16–13 | -0.04 | 9% | 18 Aug → | ||
| 13–3 | 0.02 | 10% | 18 Aug → | ||
| 10–13 | -0.00 | 8% | 16 Aug → | ||
| 10–13 | 0.01 | 20% | 16 Aug → | ||
| 10–13 | -0.05 | 6% | 16 Aug → | ||
| 13–4 | 0.08 | 13% | 16 Aug → | ||
| 9–13 | -0.05 | 8% | 16 Aug → | ||
| 13–11 | 0.01 | 17% | 15 Aug → | ||
| 11–13 | -0.03 | 10% | 15 Aug → | ||
| 16–14 | 0.04 | 11% | 15 Aug → | ||
| 13–2 | -0.04 | 15% | 14 Aug → | ||
| 16–12 | 0.04 | 9% | 14 Aug → | ||
| 8–13 | 0.03 | 12% | 14 Aug → | ||
| 13–9 | 0.00 | 12% | 14 Aug → | ||
| 7–9 | 0.06 | 22% | 14 Aug → | ||
| 13–8 | -0.06 | 8% | 13 Aug → | ||
| 13–10 | -0.01 | 9% | 13 Aug → | ||
| 7–13 | -0.06 | 6% | 12 Aug → | ||
| 6–13 | -0.04 | 16% | 12 Aug → | ||
| 6–13 | -0.05 | 9% | 11 Aug → | ||
| 13–11 | 0.02 | 13% | 11 Aug → | ||
| 13–9 | -0.06 | 11% | 11 Aug → | ||
| 9–13 | 0.02 | 12% | 11 Aug → | ||
| 13–7 | -0.05 | 9% | 11 Aug → | ||
| 13–11 | -0.01 | 19% | 11 Aug → | ||
| 14–16 | -0.03 | 9% | 10 Aug → | ||
| 5–13 | -0.10 | 6% | 10 Aug → | ||
| 15–15 | -0.05 | 14% | 10 Aug → | ||
| 3–13 | -0.05 | 11% | 10 Aug → | ||
| 13–2 | -0.07 | 22% | 9 Aug → | ||
| 13–8 | 0.01 | 16% | 9 Aug → | ||
| 5–13 | -0.02 | 19% | 9 Aug → | ||
| 13–8 | 0.04 | 7% | 9 Aug → | ||
| 11–13 | 0.01 | 12% | 9 Aug → | ||
| 13–6 | 0.10 | 21% | 9 Aug → | ||
| 1–13 | -0.07 | 4% | 8 Aug → | ||
| 13–5 | -0.05 | 3% | 8 Aug → | ||
| 7–13 | -0.00 | 14% | 8 Aug → | ||
| 16–13 | 0.06 | 9% | 8 Aug → | ||
| 13–11 | -0.04 | 6% | 8 Aug → | ||
| 4–13 | -0.07 | 11% | 7 Aug → | ||
| 13–5 | -0.03 | 3% | 7 Aug → | ||
| 13–2 | -0.05 | 14% | 7 Aug → | ||
| 13–2 | -0.01 | 15% | 7 Aug → | ||
| 4–13 | 0.01 | 14% | 6 Aug → | ||
| 6–13 | -0.01 | 18% | 6 Aug → | ||
| 3–13 | -0.02 | 12% | 6 Aug → | ||
| 9–13 | -0.01 | 20% | 6 Aug → | ||
| 5–13 | -0.00 | 11% | 6 Aug → | ||
| 13–6 | 0.04 | 13% | 5 Aug → | ||
| 3–13 | -0.04 | 8% | 5 Aug → | ||
| 6–13 | -0.03 | 13% | 5 Aug → | ||
| 13–8 | 0.01 | 10% | 5 Aug → | ||
| 13–5 | 0.01 | 5% | 4 Aug → | ||
| 13–10 | -0.01 | 16% | 4 Aug → | ||
| 7–13 | -0.04 | 21% | 4 Aug → | ||
| 13–11 | -0.03 | 4% | 3 Aug → | ||
| 7–13 | 0.03 | 17% | 1 Aug → | ||
| 13–10 | 0.07 | 12% | 1 Aug → | ||
| 9–13 | -0.03 | 14% | 31 Jul → | ||
| 13–8 | -0.03 | 9% | 31 Jul → | ||
| 13–7 | 0.00 | 15% | 31 Jul → | ||
| 13–10 | -0.04 | 9% | 31 Jul → | ||
| 9–13 | -0.03 | 18% | 30 Jul → | ||
| 15–15 | -0.04 | 17% | 30 Jul → | ||
| 11–13 | -0.01 | 9% | 29 Jul → |
Match data via Leetify.
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