🍆 𝓚𝓝𝓞𝓧𝓧 🍆 — CS2 Stats
76561198821035702[U:1:860769974]
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -30pp win rate · -0.05 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 device 92% playstyle similarity
Most alike: aim profile, opening-duel success.
Where you differ: lower 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 94 — the mechanical foundation is a clear strength.
Areas to improve
Positioning. Positioning trails aim by 42 points — deaths here waste a strong aim profile.
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
Reaction time. 563ms 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 6.6/10 (Solid), 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 |
|---|---|---|---|---|---|
| C | 28 | 10–18 | 36% | -0.00 | |
| B | 22 | 11–11 | 50% | -0.01 | |
| C | 18 | 7–11 | 39% | 0.04 | |
| D | 7 | 2–5 | 29% | 0.03 | |
| B | 6 | 3–3 | 50% | 0.01 | |
| S | 6 | 4–2 | 67% | 0.02 | |
| — | 3 | 1–2 | 33% | 0.04 | |
| office | — | 3 | 3–0 | 100% | 0.10 |
| — | 3 | 1–2 | 33% | 0.00 | |
| — | 2 | 0–2 | 0% | -0.01 | |
| — | 1 | 0–1 | 0% | 0.06 | |
| alpine | — | 1 | 0–1 | 0% | 0.05 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Anubis 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.
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 | |
|---|---|---|---|---|---|
| 11–13 | 0.00 | 29% | 23 Aug → | ||
| 1–3 | -0.14 | 0% | 22 Aug → | ||
| 10–13 | 0.02 | 28% | 20 Aug → | ||
| 7–9 | 0.13 | 50% | 20 Aug → | ||
| 6–13 | -0.02 | 28% | 15 Aug → | ||
| 6–13 | -0.04 | 38% | 6 Aug → | ||
| 13–9 | 0.02 | 67% | 6 Aug → | ||
| 5–13 | 0.02 | 41% | 2 Aug → | ||
| 13–10 | -0.04 | 21% | 31 Jul → | ||
| 13–5 | -0.06 | 27% | 30 Jul → | ||
| 8–2 | -0.04 | 67% | 30 Jul → | ||
| 11–13 | 0.07 | 39% | 25 Jul → | ||
| 0–6 | -0.06 | 0% | 24 Jul → | ||
| 7–2 | -0.03 | 58% | 24 Jul → | ||
| 5–13 | -0.00 | 36% | 24 Jul → | ||
| 5–13 | 0.02 | 26% | 24 Jul → | ||
| 13–6 | 0.09 | 35% | 23 Jul → | ||
| 13–9 | 0.18 | 25% | 23 Jul → | ||
| 13–9 | 0.07 | 38% | 23 Jul → | ||
| 13–11 | 0.05 | 34% | 21 Jul → | ||
| 12–12 | 0.01 | 46% | 20 Jul → | ||
| 13–0 | -0.02 | 27% | 20 Jul → | ||
| 0–13 | -0.02 | 100% | 20 Jul → | ||
| 3–13 | 0.06 | 56% | 20 Jul → | ||
| 6–13 | -0.03 | 48% | 19 Jul → | ||
| 13–3 | 0.05 | 26% | 19 Jul → | ||
| 6–13 | -0.06 | 18% | 18 Jul → | ||
| 13–9 | 0.01 | 21% | 17 Jul → | ||
| 13–11 | 0.08 | 26% | 17 Jul → | ||
| 13–8 | -0.03 | 33% | 16 Jul → | ||
| 6–13 | 0.13 | 40% | 16 Jul → | ||
| 3–6 | -0.05 | 40% | 29 Jun → | ||
| 13–8 | 0.08 | 48% | 29 Jun → | ||
| 13–11 | -0.01 | 18% | 24 Jun → | ||
| 13–11 | 0.01 | 23% | 24 Jun → | ||
| 13–7 | 0.02 | 43% | 23 Jun → | ||
| office | 13–7 | 0.12 | 71% | 23 Jun → | |
| 1–10 | -0.11 | 25% | 22 Jun → | ||
| alpine | 10–13 | 0.05 | 25% | 28 May → | |
| 7–13 | 0.07 | 46% | 28 May → | ||
| 5–11 | -0.03 | 36% | 20 May → | ||
| office | 13–10 | 0.08 | 63% | 19 May → | |
| 13–7 | -0.02 | 25% | 18 May → | ||
| office | 13–2 | 0.12 | 39% | 18 May → | |
| 8–13 | -0.06 | 21% | 28 Apr → | ||
| 2–5 | -0.03 | 11% | 27 Apr → | ||
| 13–16 | 0.03 | 35% | 15 Apr → | ||
| 5–2 | 0.00 | 57% | 15 Apr → | ||
| 10–13 | 0.01 | 44% | 13 Apr → | ||
| 5–13 | 0.03 | 24% | 13 Apr → | ||
| 14–16 | -0.04 | 30% | 9 Apr → | ||
| 2–13 | 0.06 | 58% | 9 Apr → | ||
| 13–6 | 0.02 | 21% | 9 Apr → | ||
| 5–13 | -0.15 | 25% | 7 Apr → | ||
| 13–3 | 0.17 | 30% | 7 Apr → | ||
| 9–13 | 0.01 | 35% | 7 Apr → | ||
| 13–11 | -0.03 | 59% | 30 Mar → | ||
| 9–4 | 0.24 | 52% | 30 Mar → | ||
| 9–2 | 0.28 | 28% | 30 Mar → | ||
| 13–8 | 0.02 | 36% | 30 Mar → | ||
| 13–6 | 0.10 | 48% | 30 Mar → | ||
| 11–13 | -0.03 | 51% | 30 Mar → | ||
| 15–15 | 0.01 | 37% | 28 Mar → | ||
| 5–13 | -0.03 | 31% | 28 Mar → | ||
| 9–13 | -0.05 | 45% | 28 Mar → | ||
| 13–3 | -0.00 | 67% | 28 Mar → | ||
| 6–13 | -0.01 | 69% | 27 Mar → | ||
| 1–7 | -0.11 | 14% | 26 Mar → | ||
| 5–13 | -0.05 | 13% | 25 Mar → | ||
| 13–11 | -0.03 | 20% | 25 Mar → | ||
| 8–13 | -0.02 | 22% | 21 Mar → | ||
| 3–13 | -0.16 | 50% | 17 Mar → | ||
| 13–10 | 0.06 | 29% | 17 Mar → | ||
| 13–7 | 0.05 | 32% | 17 Mar → | ||
| 4–13 | -0.05 | 36% | 16 Mar → | ||
| 13–3 | 0.09 | 35% | 16 Mar → | ||
| 11–13 | -0.06 | 22% | 16 Mar → | ||
| 15–15 | 0.03 | 33% | 14 Mar → | ||
| 13–9 | 0.09 | 26% | 14 Mar → | ||
| 8–13 | 0.04 | 30% | 12 Mar → | ||
| 5–13 | -0.00 | 65% | 12 Mar → | ||
| 12–12 | 0.12 | 39% | 12 Mar → | ||
| 13–10 | -0.01 | 64% | 10 Mar → | ||
| 4–13 | 0.01 | 50% | 9 Mar → | ||
| 13–7 | 0.10 | 73% | 9 Mar → | ||
| 13–9 | 0.07 | 35% | 9 Mar → | ||
| 11–13 | 0.05 | 28% | 8 Mar → | ||
| 11–13 | -0.02 | 59% | 8 Mar → | ||
| 10–13 | 0.01 | 25% | 7 Mar → | ||
| 6–13 | -0.04 | 19% | 7 Mar → | ||
| 7–13 | -0.00 | 29% | 7 Mar → | ||
| 13–9 | -0.05 | 50% | 7 Mar → | ||
| 12–16 | 0.05 | 22% | 7 Mar → | ||
| 5–13 | 0.00 | 17% | 7 Mar → | ||
| 13–2 | 0.09 | 82% | 4 Mar → | ||
| 3–13 | -0.04 | 44% | 4 Mar → | ||
| 9–13 | 0.00 | 26% | 4 Mar → | ||
| 12–16 | -0.01 | 39% | 3 Mar → | ||
| 13–7 | 0.02 | 36% | 3 Mar → | ||
| 4–13 | -0.05 | 24% | 1 Mar → |
Match data via Leetify.