Goy — CS2 Stats
76561198824151620[U:1:863885892]✓ No bans
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -20pp win rate · -0.01 avg rating
Player DNA
Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.
Strong CT-side openerLimited utility dependence
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: opening-duel success, opening-fight frequency.
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 46% on CT to 26% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 583ms 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 5.1/10 (Developing), 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 |
|---|---|---|---|---|---|
 mirage | A | 21 | 12–9 | 57% | 0.05 |
 dust2 | B | 21 | 10–11 | 48% | 0.01 |
 inferno | B | 15 | 8–7 | 53% | 0.03 |
 cache | A | 11 | 6–5 | 55% | 0.03 |
| office | A | 9 | 5–4 | 56% | 0.02 |
 vertigo | S | 7 | 5–2 | 71% | -0.01 |
 ancient | S | 6 | 5–1 | 83% | -0.00 |
 nuke | — | 4 | 1–3 | 25% | 0.04 |
 anubis | — | 4 | 2–2 | 50% | -0.01 |
 train | — | 2 | 1–1 | 50% | 0.09 |
Across the last 100 tracked matches.
Dust 2 is currently your weakest sufficiently-sampled map (48% over 21). Start with the 6 essential Dust 2 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 resultsLLLLL
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.
- Grenades & UtilityGrenade Lineups →
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.2301 — below the 0.5 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 25.801% — 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.
48% win rate across 21 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| vertigo | 8–8 | 0.00 | 22% | 16 Aug → | |
| mirage | 7–13 | 0.03 | 22% | 16 Aug → | |
| dust2 | 6–13 | -0.04 | 13% | 16 Aug → | |
| dust2 | 13–3 | 0.02 | 31% | 16 Aug → | |
| train | 6–13 | 0.08 | 12% | 15 Aug → | |
| inferno | 1–6 | -0.08 | 0% | 15 Aug → | |
| nuke | 7–8 | 0.03 | 12% | 11 Aug → | |
| cache | 9–2 | 0.08 | 28% | 9 Aug → | |
| nuke | 5–13 | 0.03 | 16% | 9 Aug → | |
| mirage | 5–13 | -0.06 | 10% | 9 Aug → | |
| dust2 | 13–3 | 0.11 | 26% | 8 Aug → | |
| mirage | 7–13 | 0.10 | 16% | 8 Aug → | |
| mirage | 13–8 | 0.06 | 8% | 4 Aug → | |
| dust2 | 13–10 | 0.06 | 12% | 2 Aug → | |
| inferno | 9–13 | -0.08 | 19% | 2 Aug → | |
| anubis | 11–13 | -0.01 | 8% | 30 Jul → | |
| cache | 13–6 | 0.05 | 25% | 29 Jul → | |
| cache | 3–13 | -0.02 | 12% | 28 Jul → | |
| cache | 5–13 | -0.02 | 17% | 26 Jul → | |
| dust2 | 6–13 | -0.05 | 24% | 25 Jul → | |
| anubis | 13–9 | -0.02 | 14% | 22 Jul → | |
| vertigo | 13–9 | -0.04 | 18% | 22 Jul → | |
| dust2 | 13–7 | 0.12 | 20% | 19 Jul → | |
| mirage | 13–4 | 0.15 | 8% | 15 Jul → | |
| ancient | 13–11 | 0.00 | 17% | 15 Jul → | |
| ancient | 13–8 | -0.00 | 14% | 11 Jul → | |
| mirage | 13–11 | 0.10 | 17% | 11 Jul → | |
| dust2 | 5–13 | -0.03 | 9% | 11 Jul → | |
| mirage | 2–13 | 0.01 | 17% | 9 Jul → | |
| office | 13–11 | 0.06 | 23% | 9 Jul → | |
| mirage | 13–3 | 0.03 | 24% | 9 Jul → | |
| mirage | 7–13 | 0.17 | 14% | 6 Jul → | |
| office | 11–13 | 0.06 | 9% | 5 Jul → | |
| inferno | 12–12 | 0.01 | 15% | 5 Jul → | |
| mirage | 13–1 | 0.11 | 24% | 5 Jul → | |
| dust2 | 13–3 | -0.08 | 20% | 3 Jul → | |
| office | 13–8 | -0.01 | 16% | 1 Jul → | |
| mirage | 13–10 | 0.01 | 16% | 1 Jul → | |
| dust2 | 10–13 | 0.01 | 7% | 30 Jun → | |
| inferno | 13–1 | 0.21 | 31% | 29 Jun → | |
| office | 8–13 | -0.02 | 30% | 28 Jun → | |
| vertigo | 13–7 | 0.04 | 11% | 28 Jun → | |
| cache | 13–9 | 0.05 | 14% | 28 Jun → | |
| dust2 | 13–4 | -0.03 | 8% | 19 Jun → | |
| office | 13–3 | 0.10 | 14% | 18 Jun → | |
| mirage | 13–11 | 0.04 | 27% | 15 Jun → | |
| dust2 | 4–13 | -0.04 | 23% | 14 Jun → | |
| ancient | 13–5 | 0.00 | 21% | 14 Jun → | |
| mirage | 13–7 | 0.09 | 8% | 14 Jun → | |
| cache | 13–5 | 0.04 | 16% | 14 Jun → | |
| cache | 7–13 | -0.05 | 6% | 14 Jun → | |
| dust2 | 1–13 | -0.05 | 33% | 14 Jun → | |
| inferno | 13–4 | 0.01 | 24% | 10 Jun → | |
| mirage | 13–2 | 0.06 | 13% | 9 Jun → | |
| inferno | 13–0 | 0.00 | 17% | 6 Jun → | |
| ancient | 13–5 | 0.02 | 15% | 6 Jun → | |
| dust2 | 13–2 | -0.03 | 8% | 4 Jun → | |
| dust2 | 0–13 | -0.06 | 24% | 4 Jun → | |
| mirage | 13–3 | -0.02 | 11% | 3 Jun → | |
| ancient | 13–4 | -0.06 | 19% | 2 Jun → | |
| vertigo | 13–9 | 0.01 | 23% | 29 May → | |
| mirage | 4–0 | 0.02 | 6% | 28 May → | |
| inferno | 4–13 | 0.01 | 14% | 26 May → | |
| mirage | 12–12 | 0.02 | 24% | 25 May → | |
| mirage | 12–12 | -0.03 | 23% | 24 May → | |
| mirage | 13–9 | 0.10 | 17% | 24 May → | |
| inferno | 16–13 | 0.02 | 16% | 20 May → | |
| cache | 13–11 | 0.08 | 18% | 17 May → | |
| dust2 | 13–8 | -0.01 | 24% | 17 May → | |
| cache | 13–9 | -0.02 | 16% | 17 May → | |
| office | 13–10 | -0.01 | 21% | 17 May → | |
| mirage | 6–13 | -0.04 | 14% | 16 May → | |
| office | 13–4 | 0.02 | 14% | 15 May → | |
| cache | 7–13 | 0.08 | 25% | 7 May → | |
| dust2 | 13–9 | 0.06 | 12% | 3 May → | |
| cache | 6–13 | 0.04 | 13% | 29 Apr → | |
| nuke | 13–8 | 0.08 | 19% | 26 Apr → | |
| dust2 | 11–13 | -0.05 | 17% | 26 Apr → | |
| dust2 | 13–16 | -0.03 | 17% | 26 Apr → | |
| train | 6–0 | 0.09 | 83% | 25 Apr → | |
| dust2 | 13–0 | 0.17 | 23% | 20 Apr → | |
| dust2 | 12–12 | 0.07 | 14% | 19 Apr → | |
| vertigo | 9–7 | -0.10 | 3% | 11 Apr → | |
| nuke | 7–9 | 0.03 | 4% | 11 Apr → | |
| inferno | 9–3 | 0.17 | 9% | 11 Apr → | |
| inferno | 2–13 | -0.05 | 11% | 11 Apr → | |
| vertigo | 13–4 | 0.08 | 21% | 11 Apr → | |
| vertigo | 6–13 | -0.04 | 16% | 11 Apr → | |
| inferno | 9–6 | -0.02 | 7% | 8 Apr → | |
| inferno | 9–7 | 0.02 | 15% | 7 Apr → | |
| inferno | 9–2 | 0.24 | 38% | 6 Apr → | |
| inferno | 8–8 | 0.04 | 19% | 6 Apr → | |
| anubis | 12–5 | -0.01 | 14% | 5 Apr → | |
| office | 9–13 | -0.05 | 12% | 18 Mar → | |
| dust2 | 6–13 | 0.02 | 21% | 7 Mar → | |
| mirage | 11–13 | 0.03 | 19% | 7 Mar → | |
| anubis | 11–13 | 0.02 | 13% | 8 Feb → | |
| ancient | 7–13 | 0.03 | 13% | 6 Feb → | |
| office | 11–13 | 0.07 | 20% | 22 Jan → | |
| inferno | 7–13 | 0.01 | 9% | 17 Jan → |
Match data via Leetify.