uᴉSʇoN — CS2 Stats
CA76561198149189231[U:1:188923503]Steam profile ↗
Share this profile
The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +10pp win rate · -0.00 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 80% playstyle similarity
Most alike: opening-fight frequency, positioning profile.
Where you differ: lower aim profile; 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
Areas to improve
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
T-side openings. Opening success drops from 55% on CT to 11% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 674ms 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 5.6/10 (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 |
|---|---|---|---|---|---|
| B | 27 | 14–13 | 52% | 0.02 | |
| C | 24 | 10–14 | 42% | 0.03 | |
| S | 12 | 10–2 | 83% | 0.02 | |
| D | 10 | 2–8 | 20% | 0.03 | |
| D | 7 | 1–6 | 14% | 0.03 | |
| A | 5 | 3–2 | 60% | 0.04 | |
| — | 3 | 3–0 | 100% | 0.05 | |
| — | 3 | 3–0 | 100% | 0.06 | |
| tuscan | — | 3 | 1–2 | 33% | -0.02 |
| — | 2 | 0–2 | 0% | 0.03 | |
| breach | — | 2 | 1–1 | 50% | 0.12 |
| boulder | — | 1 | 1–0 | 100% | -0.07 |
| insertion2 | — | 1 | 1–0 | 100% | 0.07 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (14% over 7). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsLLWWL
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.
- 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 10.8414% — 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.
14% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| boulder | 13–3 | -0.07 | 8% | 9 Aug → | |
| 13–7 | 0.01 | 25% | 9 Aug → | ||
| 5–13 | -0.04 | 20% | 9 Aug → | ||
| 16–14 | -0.02 | 18% | 5 Jul → | ||
| 8–13 | -0.00 | 15% | 5 Jul → | ||
| 13–5 | -0.04 | 16% | 2 May → | ||
| 7–13 | -0.03 | 19% | 2 May → | ||
| 13–7 | 0.17 | 36% | 9 Mar → | ||
| 13–6 | 0.17 | 31% | 9 Mar → | ||
| 12–12 | -0.01 | 26% | 3 Jan → | ||
| 13–4 | 0.05 | 38% | 3 Jan → | ||
| 13–9 | 0.01 | 22% | 7 Dec → | ||
| 13–6 | 0.07 | 29% | 7 Dec → | ||
| 9–13 | -0.06 | 24% | 9 Sept → | ||
| 3–13 | -0.08 | 19% | 9 Sept → | ||
| 13–11 | -0.01 | 18% | 9 Sept → | ||
| 9–5 | 0.08 | 42% | 5 Sept → | ||
| 6–9 | 0.13 | 18% | 5 Sept → | ||
| 6–16 | -0.03 | 24% | 30 May → | ||
| 15–15 | 0.02 | 13% | 13 May → | ||
| 16–7 | 0.02 | 25% | 13 May → | ||
| 5–9 | 0.02 | 30% | 13 May → | ||
| 15–15 | 0.01 | 21% | 13 May → | ||
| 16–10 | -0.02 | 19% | 11 May → | ||
| 13–16 | -0.00 | 13% | 11 May → | ||
| 16–14 | 0.05 | 17% | 11 May → | ||
| 8–8 | -0.03 | 6% | 8 May → | ||
| 9–2 | 0.09 | 25% | 8 May → | ||
| 9–3 | 0.04 | 6% | 8 May → | ||
| 16–9 | 0.02 | 14% | 6 May → | ||
| 16–13 | 0.09 | 21% | 6 May → | ||
| 16–8 | 0.08 | 15% | 6 May → | ||
| 15–15 | -0.02 | 17% | 6 May → | ||
| 14–16 | 0.02 | 24% | 6 May → | ||
| 15–15 | 0.04 | 20% | 30 Apr → | ||
| 16–11 | 0.05 | 27% | 30 Apr → | ||
| 9–7 | 0.10 | 27% | 27 Apr → | ||
| 8–8 | 0.07 | 15% | 26 Apr → | ||
| 6–9 | 0.08 | 18% | 26 Apr → | ||
| 9–16 | 0.03 | 17% | 24 Apr → | ||
| 8–16 | -0.03 | 23% | 24 Apr → | ||
| 16–14 | -0.02 | 13% | 10 Apr → | ||
| 10–16 | -0.00 | 15% | 10 Apr → | ||
| 16–8 | 0.08 | 23% | 9 Apr → | ||
| 11–16 | 0.03 | 11% | 9 Apr → | ||
| 16–12 | -0.02 | 18% | 9 Apr → | ||
| 14–16 | 0.04 | 12% | 8 Apr → | ||
| 16–12 | 0.01 | 15% | 8 Apr → | ||
| 9–16 | 0.06 | 14% | 8 Apr → | ||
| 16–12 | 0.13 | 24% | 7 Apr → | ||
| 15–15 | 0.06 | 30% | 7 Apr → | ||
| 15–15 | -0.05 | 20% | 7 Apr → | ||
| 16–13 | -0.00 | 24% | 26 Mar → | ||
| 13–16 | 0.06 | 14% | 26 Mar → | ||
| 11–16 | 0.02 | 22% | 26 Mar → | ||
| 11–16 | -0.01 | 20% | 26 Mar → | ||
| 14–16 | 0.03 | 15% | 26 Feb → | ||
| 16–5 | 0.02 | 11% | 26 Feb → | ||
| 16–10 | 0.13 | 18% | 26 Feb → | ||
| 2–16 | -0.05 | 17% | 26 Feb → | ||
| 16–11 | -0.03 | 21% | 19 Feb → | ||
| 14–16 | 0.06 | 10% | 19 Feb → | ||
| 15–15 | 0.05 | 18% | 19 Feb → | ||
| 16–10 | 0.02 | 22% | 31 Dec → | ||
| 16–9 | 0.14 | 14% | 2 Oct → | ||
| breach | 5–16 | 0.21 | 29% | 28 Aug → | |
| 16–6 | 0.08 | 11% | 24 Aug → | ||
| 16–10 | -0.03 | 9% | 24 Aug → | ||
| breach | 16–0 | 0.03 | 0% | 24 Aug → | |
| 9–16 | 0.05 | 18% | 24 Aug → | ||
| 16–9 | 0.06 | 13% | 23 Aug → | ||
| 16–9 | 0.05 | 21% | 23 Aug → | ||
| 9–16 | -0.03 | 19% | 23 Aug → | ||
| tuscan | 7–16 | -0.01 | 16% | 23 Aug → | |
| 16–11 | -0.02 | 24% | 23 Aug → | ||
| tuscan | 8–16 | -0.02 | 23% | 21 Aug → | |
| tuscan | 16–1 | -0.03 | 6% | 21 Aug → | |
| 15–15 | -0.01 | 14% | 6 Jun → | ||
| 6–16 | -0.03 | 13% | 26 Mar → | ||
| 16–6 | 0.04 | 18% | 17 Mar → | ||
| 6–16 | 0.01 | 21% | 13 Mar → | ||
| 7–16 | 0.02 | 26% | 13 Mar → | ||
| 5–9 | 0.06 | 22% | 5 Mar → | ||
| 9–5 | 0.04 | 33% | 5 Mar → | ||
| 16–13 | -0.02 | 21% | 12 Feb → | ||
| 9–7 | 0.02 | 23% | 5 Feb → | ||
| 9–7 | -0.03 | 20% | 5 Feb → | ||
| 9–7 | 0.08 | 10% | 24 Jan → | ||
| insertion2 | 16–8 | 0.07 | 29% | 20 Jan → | |
| 9–7 | 0.13 | 22% | 19 Jan → | ||
| 10–16 | 0.04 | 18% | 17 Jan → | ||
| 15–15 | 0.02 | 13% | 16 Jan → | ||
| 16–10 | 0.06 | 19% | 13 Jan → | ||
| 16–9 | 0.08 | 22% | 13 Jan → | ||
| 12–16 | -0.01 | 19% | 13 Jan → | ||
| 13–16 | 0.07 | 24% | 9 Jan → | ||
| 10–16 | 0.01 | 9% | 8 Jan → | ||
| 6–16 | 0.07 | 24% | 8 Jan → | ||
| 8–8 | 0.03 | 13% | 1 Jan → | ||
| 16–12 | -0.04 | 20% | 25 Dec → |
Match data via Leetify.