Gizelli — CS2 Stats
76561198054308589[U:1:94042861]✓ No bans
How this compares with the same rank
Median values for Level 10 among CSDB-tracked players (n=218), 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 | 54.3% | 52.8% |
| Shot accuracy | 19.9% | 13.7% |
| Kill/death ratio | 1.95 | 1.08 |
| Match win rate | 45.5% | 49.2% |
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -10pp win rate · +0.01 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 sh1ro 96% 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 91 — the mechanical foundation is a clear strength.
CT openings. 69% 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 69% 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 7.7/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.00 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 |
|---|---|---|---|---|---|
| S | 21 | 14–7 | 67% | 0.05 | |
| B | 21 | 11–10 | 52% | 0.03 | |
| S | 15 | 13–2 | 87% | 0.07 | |
| A | 13 | 8–5 | 62% | 0.06 | |
| S | 12 | 8–4 | 67% | 0.04 | |
| A | 8 | 5–3 | 63% | 0.04 | |
| D | 5 | 1–4 | 20% | 0.02 | |
| — | 4 | 3–1 | 75% | 0.05 | |
| — | 1 | 0–1 | 0% | -0.04 |
Across the last 100 tracked matches.
Ancient is currently your weakest sufficiently-sampled map (20% over 5). 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 resultsWLWLW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 176 | 55% | 1.43 | 19.1 |
| Inferno | 159 | 54% | 1.36 | 18.3 |
| Ancient | 56 | 48% | 1.37 | 18.2 |
| Dust2 | 52 | 56% | 1.38 | 18.4 |
| Nuke | 32 | 41% | 1.30 | 17.0 |
| Train | 29 | 48% | 1.43 | 19.0 |
| Overpass | 26 | 50% | 1.39 | 18.5 |
| Anubis | 22 | 50% | 1.29 | 18.8 |
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.
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 | |
|---|---|---|---|---|---|
| 13–5 | 0.04 | 40% | 15 Jun → | ||
| 13–2 | 0.27 | 32% | 30 Apr → | ||
| 13–2 | 0.06 | 25% | 30 Apr → | ||
| 13–1 | 0.03 | 17% | 30 Apr → | ||
| 13–0 | 0.17 | 38% | 30 Apr → | ||
| 9–13 | -0.04 | 13% | 30 Apr → | ||
| 10–13 | -0.01 | 16% | 28 Apr → | ||
| 16–13 | 0.05 | 17% | 28 Apr → | ||
| 13–11 | 0.05 | 22% | 27 Apr → | ||
| 16–13 | 0.01 | 23% | 27 Apr → | ||
| 8–13 | -0.06 | 22% | 27 Apr → | ||
| 13–4 | 0.07 | 19% | 27 Apr → | ||
| 10–0 | 0.12 | 15% | 26 Apr → | ||
| 13–9 | 0.03 | 16% | 26 Apr → | ||
| 16–14 | 0.03 | 25% | 26 Apr → | ||
| 19–16 | 0.04 | 22% | 26 Apr → | ||
| 13–4 | 0.08 | 17% | 26 Apr → | ||
| 13–4 | 0.04 | 30% | 25 Apr → | ||
| 13–4 | 0.06 | 31% | 25 Apr → | ||
| 13–10 | 0.07 | 30% | 25 Apr → | ||
| 13–11 | 0.02 | 18% | 25 Apr → | ||
| 16–14 | -0.05 | 19% | 25 Apr → | ||
| 16–13 | 0.02 | 25% | 25 Apr → | ||
| 13–4 | 0.09 | 38% | 25 Apr → | ||
| 11–13 | -0.03 | 14% | 25 Apr → | ||
| 13–9 | 0.06 | 17% | 25 Apr → | ||
| 13–9 | 0.02 | 17% | 25 Apr → | ||
| 13–2 | 0.06 | 20% | 25 Apr → | ||
| 13–8 | 0.05 | 22% | 24 Apr → | ||
| 13–10 | 0.07 | 31% | 24 Apr → | ||
| 9–13 | -0.00 | 21% | 24 Apr → | ||
| 16–14 | 0.07 | 26% | 23 Apr → | ||
| 7–13 | 0.03 | 28% | 23 Apr → | ||
| 13–4 | 0.08 | 15% | 23 Apr → | ||
| 10–13 | 0.09 | 18% | 16 Apr → | ||
| 13–11 | 0.06 | 25% | 16 Apr → | ||
| 13–10 | -0.03 | 19% | 16 Apr → | ||
| 13–11 | 0.04 | 21% | 16 Apr → | ||
| 9–13 | 0.11 | 27% | 15 Apr → | ||
| 13–4 | 0.04 | 4% | 15 Apr → | ||
| 13–9 | 0.05 | 21% | 15 Apr → | ||
| 11–13 | 0.09 | 19% | 14 Apr → | ||
| 11–13 | 0.01 | 22% | 14 Apr → | ||
| 5–13 | 0.08 | 24% | 13 Apr → | ||
| 4–13 | -0.01 | 17% | 13 Apr → | ||
| 13–11 | 0.01 | 24% | 12 Apr → | ||
| 13–9 | 0.03 | 27% | 11 Apr → | ||
| 13–7 | 0.05 | 54% | 11 Apr → | ||
| 13–11 | 0.07 | 25% | 11 Apr → | ||
| 13–7 | 0.14 | 20% | 10 Apr → | ||
| 11–13 | 0.08 | 35% | 9 Apr → | ||
| 13–5 | 0.15 | 24% | 8 Apr → | ||
| 13–9 | 0.09 | 21% | 7 Apr → | ||
| 13–6 | 0.10 | 33% | 7 Apr → | ||
| 10–13 | 0.02 | 11% | 7 Apr → | ||
| 13–8 | 0.01 | 17% | 6 Apr → | ||
| 10–13 | -0.01 | 15% | 6 Apr → | ||
| 9–13 | -0.00 | 20% | 25 Mar → | ||
| 13–11 | 0.04 | 19% | 25 Mar → | ||
| 12–16 | 0.03 | 28% | 19 Mar → | ||
| 17–19 | 0.03 | 28% | 19 Mar → | ||
| 10–13 | 0.01 | 19% | 26 Feb → | ||
| 13–5 | 0.05 | 21% | 26 Feb → | ||
| 13–7 | 0.06 | 21% | 25 Feb → | ||
| 10–13 | 0.01 | 11% | 25 Feb → | ||
| 13–11 | -0.02 | 17% | 25 Feb → | ||
| 13–6 | 0.08 | 26% | 25 Feb → | ||
| 13–2 | 0.04 | 24% | 25 Feb → | ||
| 13–2 | 0.14 | 18% | 25 Feb → | ||
| 13–3 | 0.09 | 31% | 25 Feb → | ||
| 13–6 | 0.05 | 21% | 18 Feb → | ||
| 9–13 | 0.03 | 20% | 18 Feb → | ||
| 9–13 | 0.06 | 25% | 2 Feb → | ||
| 6–13 | 0.01 | 28% | 2 Feb → | ||
| 13–1 | 0.05 | 17% | 1 Feb → | ||
| 3–13 | -0.05 | 20% | 1 Feb → | ||
| 11–13 | 0.01 | 21% | 1 Feb → | ||
| 13–10 | 0.01 | 16% | 1 Feb → | ||
| 13–6 | 0.09 | 25% | 1 Feb → | ||
| 9–13 | 0.04 | 22% | 1 Feb → | ||
| 11–13 | 0.13 | 29% | 1 Feb → | ||
| 13–10 | 0.03 | 26% | 31 Jan → | ||
| 11–13 | 0.03 | 27% | 31 Jan → | ||
| 10–13 | 0.05 | 18% | 31 Jan → | ||
| 13–7 | 0.03 | 12% | 31 Jan → | ||
| 11–13 | 0.03 | 29% | 30 Jan → | ||
| 13–8 | 0.05 | 29% | 30 Jan → | ||
| 13–10 | 0.09 | 32% | 30 Jan → | ||
| 13–1 | 0.26 | 42% | 30 Jan → | ||
| 11–13 | 0.01 | 23% | 24 Jan → | ||
| 7–13 | 0.01 | 25% | 24 Jan → | ||
| 13–16 | 0.02 | 14% | 23 Jan → | ||
| 16–14 | 0.04 | 20% | 15 Jan → | ||
| 13–8 | 0.08 | 31% | 15 Jan → | ||
| 17–19 | 0.02 | 21% | 14 Jan → | ||
| 13–7 | 0.04 | 16% | 12 Jan → | ||
| 16–19 | -0.04 | 16% | 8 Jan → | ||
| 7–13 | -0.03 | 17% | 8 Jan → | ||
| 13–10 | 0.01 | 21% | 8 Jan → | ||
| 4–13 | 0.01 | 15% | 8 Jan → |
Match data via Leetify.
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