ZazzleZ — CS2 Stats
DE76561198125103622[U:1:164837894]Steam profile ↗
How this compares with the same rank
Median values for Level 10 among CSDB-tracked players (n=4,917), 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 | 57.0% | 51.9% |
| Shot accuracy | 14.5% | 13.7% |
| Kill/death ratio | 1.01 | 1.08 |
| Match win rate | 48.2% | 48.7% |
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -40pp win rate · -0.03 avg rating
Player DNA
Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.
Strong 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 93% playstyle similarity
Most alike: opening-fight frequency, utility contribution.
Where you differ: 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
Strengths
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 44% 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 7.3/10 (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 | 23 | 14–9 | 61% | 0.03 | |
| C | 16 | 7–9 | 44% | 0.03 | |
| S | 15 | 11–4 | 73% | 0.07 | |
| B | 12 | 6–6 | 50% | 0.05 | |
| D | 7 | 2–5 | 29% | 0.00 | |
| C | 7 | 3–4 | 43% | 0.05 | |
| C | 5 | 2–3 | 40% | 0.02 | |
| — | 4 | 0–4 | 0% | -0.02 | |
| — | 3 | 3–0 | 100% | 0.17 | |
| office | — | 2 | 2–0 | 100% | 0.08 |
| agency | — | 2 | 1–1 | 50% | 0.03 |
| jura | — | 2 | 1–1 | 50% | 0.07 |
| alpine | — | 1 | 1–0 | 100% | 0.04 |
| — | 1 | 0–1 | 0% | 0.07 |
Across the last 100 tracked matches.
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
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Nuke | 203 | 62% | 1.38 | 20.1 |
| Ancient | 172 | 56% | 1.32 | 19.9 |
| Anubis | 167 | 55% | 1.34 | 20.8 |
| Inferno | 93 | 41% | 1.25 | 19.9 |
| Overpass | 82 | 55% | 1.39 | 20.6 |
| Vertigo | 45 | 71% | 1.64 | 21.2 |
| Train | 35 | 46% | 1.46 | 19.8 |
| Cache | 34 | 41% | 1.16 | 19.4 |
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.
29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–2 | 0.01 | 20% | 16 Aug → | ||
| 6–13 | -0.02 | 17% | 16 Aug → | ||
| 5–13 | 0.04 | 30% | 16 Aug → | ||
| 10–13 | -0.06 | 33% | 16 Aug → | ||
| 15–19 | 0.06 | 22% | 7 Aug → | ||
| 15–19 | -0.03 | 27% | 26 Jul → | ||
| 13–3 | 0.03 | 24% | 25 Jul → | ||
| 11–13 | -0.01 | 19% | 25 Jul → | ||
| 7–13 | 0.02 | 22% | 25 Jul → | ||
| 16–13 | 0.04 | 23% | 22 Jul → | ||
| 13–7 | 0.04 | 22% | 19 Jul → | ||
| 9–13 | 0.05 | 18% | 18 Jul → | ||
| 13–10 | -0.05 | 41% | 7 Jul → | ||
| 13–8 | 0.03 | 24% | 6 Jul → | ||
| 13–8 | 0.07 | 24% | 3 Jul → | ||
| 13–9 | 0.08 | 36% | 3 Jul → | ||
| 13–7 | 0.06 | 21% | 28 Jun → | ||
| 3–13 | -0.04 | 15% | 26 May → | ||
| 10–13 | 0.05 | 34% | 26 May → | ||
| 7–1 | 0.11 | 27% | 26 May → | ||
| 9–13 | -0.02 | 21% | 14 May → | ||
| 12–16 | 0.02 | 23% | 13 May → | ||
| 11–13 | 0.04 | 28% | 11 May → | ||
| 13–8 | 0.16 | 16% | 1 May → | ||
| 13–4 | 0.04 | 16% | 29 Apr → | ||
| 16–13 | 0.06 | 19% | 27 Apr → | ||
| 13–8 | 0.08 | 25% | 26 Apr → | ||
| 13–8 | -0.00 | 17% | 26 Apr → | ||
| 11–13 | 0.03 | 16% | 25 Apr → | ||
| 13–4 | 0.11 | 31% | 24 Apr → | ||
| 11–13 | 0.02 | 12% | 23 Apr → | ||
| 9–13 | 0.04 | 14% | 23 Apr → | ||
| 13–10 | 0.07 | 26% | 13 Apr → | ||
| 13–4 | 0.11 | 29% | 9 Apr → | ||
| 13–1 | 0.13 | 32% | 9 Apr → | ||
| 13–5 | 0.05 | 41% | 24 Mar → | ||
| 15–15 | 0.01 | 22% | 19 Mar → | ||
| 3–13 | 0.03 | 18% | 19 Mar → | ||
| alpine | 13–2 | 0.04 | 38% | 18 Mar → | |
| office | 13–8 | 0.07 | 32% | 18 Mar → | |
| 8–13 | 0.01 | 21% | 14 Mar → | ||
| 6–13 | -0.02 | 31% | 14 Mar → | ||
| 13–8 | 0.02 | 18% | 14 Mar → | ||
| 13–11 | 0.02 | 12% | 13 Mar → | ||
| 7–13 | 0.03 | 28% | 13 Mar → | ||
| 13–5 | 0.03 | 24% | 13 Mar → | ||
| 13–2 | 0.12 | 31% | 13 Mar → | ||
| 13–6 | 0.06 | 19% | 13 Mar → | ||
| 16–12 | 0.07 | 25% | 12 Mar → | ||
| 13–8 | 0.14 | 27% | 12 Mar → | ||
| 13–5 | 0.04 | 20% | 12 Mar → | ||
| 14–16 | 0.07 | 22% | 12 Mar → | ||
| 10–13 | 0.02 | 17% | 8 Mar → | ||
| 4–13 | -0.01 | 26% | 21 Nov → | ||
| 11–13 | -0.04 | 19% | 31 Oct → | ||
| 8–13 | 0.06 | 33% | 17 Oct → | ||
| 13–4 | 0.18 | 17% | 17 Oct → | ||
| 13–11 | 0.10 | 24% | 15 Oct → | ||
| 13–9 | 0.14 | 27% | 15 Oct → | ||
| 13–4 | 0.03 | 23% | 15 Oct → | ||
| 13–10 | -0.02 | 20% | 12 Oct → | ||
| 8–13 | 0.03 | 28% | 11 Oct → | ||
| 13–7 | 0.05 | 26% | 11 Oct → | ||
| 17–19 | 0.05 | 14% | 6 Oct → | ||
| office | 13–7 | 0.09 | 26% | 1 Oct → | |
| 11–13 | 0.04 | 35% | 24 Sept → | ||
| 13–4 | 0.05 | 20% | 24 Sept → | ||
| 13–5 | 0.13 | 17% | 24 Sept → | ||
| 10–13 | 0.11 | 18% | 22 Sept → | ||
| 13–10 | -0.03 | 34% | 22 Sept → | ||
| 11–13 | 0.04 | 34% | 15 Sept → | ||
| 8–13 | -0.05 | 23% | 3 Sept → | ||
| 13–8 | 0.10 | 35% | 30 Aug → | ||
| 13–16 | -0.00 | 24% | 27 Aug → | ||
| 9–1 | 0.27 | 15% | 11 Aug → | ||
| 13–6 | 0.08 | 30% | 10 Aug → | ||
| 2–13 | -0.03 | 11% | 8 Aug → | ||
| 13–9 | 0.04 | 24% | 7 Aug → | ||
| agency | 4–13 | 0.01 | 15% | 6 Aug → | |
| agency | 13–4 | 0.05 | 24% | 6 Aug → | |
| jura | 12–12 | 0.02 | 17% | 5 Aug → | |
| jura | 13–1 | 0.12 | 17% | 5 Aug → | |
| 4–13 | -0.03 | 24% | 28 Jul → | ||
| 14–16 | -0.00 | 16% | 16 Jul → | ||
| 13–2 | 0.17 | 21% | 4 Jul → | ||
| 5–13 | 0.03 | 19% | 2 Jul → | ||
| 9–13 | 0.04 | 27% | 24 Jun → | ||
| 12–16 | -0.01 | 28% | 15 Jun → | ||
| 13–5 | 0.05 | 26% | 10 Jun → | ||
| 13–3 | 0.14 | 14% | 24 May → | ||
| 5–13 | -0.05 | 27% | 6 May → | ||
| 11–13 | 0.04 | 8% | 16 Apr → | ||
| 13–11 | 0.03 | 28% | 16 Apr → | ||
| 13–1 | 0.08 | 23% | 15 Apr → | ||
| 13–5 | 0.07 | 17% | 13 Apr → | ||
| 1–13 | -0.06 | 27% | 13 Apr → | ||
| 4–13 | -0.04 | 21% | 12 Apr → | ||
| 13–5 | 0.05 | 17% | 8 Apr → | ||
| 7–13 | -0.02 | 28% | 4 Apr → | ||
| 3–13 | -0.03 | 31% | 4 Apr → |
Match data via Leetify.
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