GoldenDrew — CS2 Stats
76561198202408025[U:1:242142297]
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: +40pp win rate · -0.02 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 58% playstyle similarity
Most alike: opening-duel success, positioning profile.
Where you differ: lower utility contribution; 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
Areas to improve
Reaction time. 665ms 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 2.8/10 (Learning), 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 |
|---|---|---|---|---|---|
| D | 22 | 5–17 | 23% | -0.08 | |
| D | 16 | 5–11 | 31% | -0.07 | |
| B | 11 | 5–6 | 45% | -0.04 | |
| B | 11 | 5–6 | 45% | -0.06 | |
| office | D | 6 | 0–6 | 0% | -0.03 |
| B | 6 | 3–3 | 50% | -0.09 | |
| B | 6 | 3–3 | 50% | -0.05 | |
| C | 5 | 2–3 | 40% | -0.05 | |
| — | 4 | 4–0 | 100% | -0.04 | |
| — | 2 | 0–2 | 0% | -0.12 | |
| assembly | — | 2 | 0–2 | 0% | -0.11 |
| — | 1 | 1–0 | 100% | -0.06 | |
| warden | — | 1 | 1–0 | 100% | -0.07 |
| jura | — | 1 | 0–1 | 0% | -0.11 |
| grail | — | 1 | 1–0 | 100% | -0.06 |
| edin | — | 1 | 0–1 | 0% | -0.02 |
| palais | — | 1 | 1–0 | 100% | -0.05 |
| italy | — | 1 | 0–1 | 0% | -0.11 |
| mills | — | 1 | 0–1 | 0% | -0.07 |
| memento | — | 1 | 0–1 | 0% | -0.19 |
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 resultsWLWLW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Inferno | 2 | 100% | 0.72 | 8.0 |
| Dust2 | 2 | 50% | 0.55 | 11.0 |
| Mirage | 1 | 100% | 0.91 | 10.0 |
| Anubis | 1 | 100% | 0.69 | 11.0 |
| Nuke | 1 | 0% | 0.39 | 7.0 |
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 MechanicsAim Training →
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 12.0186° — above the 12° mark we flag
- 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 0.157 — below the 0.5 mark we flag
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
23% win rate across 22 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 5–13 | -0.13 | 33% | 11 Jul → | ||
| 13–10 | -0.05 | 30% | 28 Jun → | ||
| 13–10 | -0.06 | 7% | 2 May → | ||
| 13–11 | 0.00 | 14% | 25 Apr → | ||
| 12–12 | -0.03 | 16% | 25 Apr → | ||
| 9–6 | -0.13 | 11% | 16 Apr → | ||
| 13–11 | -0.06 | 25% | 3 Apr → | ||
| 12–12 | -0.05 | 18% | 26 Mar → | ||
| warden | 13–10 | -0.07 | 19% | 1 Mar → | |
| 13–9 | -0.06 | 31% | 30 Aug → | ||
| 11–13 | -0.08 | 17% | 21 Aug → | ||
| 13–4 | 0.02 | 12% | 2 Aug → | ||
| office | 8–13 | -0.01 | 26% | 27 Jul → | |
| 8–13 | 0.05 | 28% | 27 Jul → | ||
| 5–13 | -0.10 | 24% | 17 Jul → | ||
| office | 12–12 | -0.06 | 13% | 17 Jul → | |
| 13–11 | -0.11 | 9% | 17 Jul → | ||
| 11–13 | -0.06 | 26% | 28 Jun → | ||
| 13–10 | -0.04 | 31% | 28 Jun → | ||
| 11–13 | -0.06 | 18% | 27 Jun → | ||
| 5–13 | -0.10 | 0% | 27 May → | ||
| 12–12 | -0.08 | 11% | 16 May → | ||
| jura | 11–13 | -0.11 | 24% | 11 May → | |
| grail | 13–11 | -0.06 | 17% | 11 May → | |
| 7–9 | -0.14 | 9% | 7 May → | ||
| 3–13 | -0.02 | 15% | 26 Apr → | ||
| 13–10 | -0.04 | 30% | 18 Apr → | ||
| 13–10 | -0.03 | 15% | 18 Apr → | ||
| 3–13 | -0.09 | 5% | 6 Apr → | ||
| office | 7–13 | -0.05 | 22% | 5 Apr → | |
| 13–11 | -0.04 | 17% | 5 Apr → | ||
| 7–9 | -0.00 | 13% | 28 Mar → | ||
| 3–13 | -0.05 | 7% | 23 Mar → | ||
| 6–13 | -0.10 | 10% | 23 Mar → | ||
| 8–13 | -0.08 | 25% | 23 Mar → | ||
| 4–9 | -0.10 | 24% | 8 Mar → | ||
| 7–9 | -0.09 | 20% | 3 Mar → | ||
| 13–6 | -0.03 | 17% | 3 Mar → | ||
| office | 10–13 | -0.04 | 5% | 2 Mar → | |
| 10–13 | -0.07 | 26% | 2 Mar → | ||
| 3–13 | -0.08 | 7% | 1 Mar → | ||
| 8–8 | -0.06 | 19% | 24 Feb → | ||
| 4–9 | -0.13 | 9% | 24 Feb → | ||
| 9–5 | -0.10 | 8% | 23 Feb → | ||
| 7–9 | -0.01 | 10% | 22 Feb → | ||
| 7–9 | -0.14 | 27% | 22 Feb → | ||
| 3–13 | -0.13 | 11% | 25 Jan → | ||
| 16–14 | -0.04 | 17% | 8 Jan → | ||
| 4–13 | -0.11 | 30% | 23 Nov → | ||
| edin | 4–13 | -0.02 | 7% | 16 Nov → | |
| 8–13 | -0.07 | 22% | 16 Nov → | ||
| palais | 9–4 | -0.05 | 22% | 15 Nov → | |
| 10–13 | -0.05 | 29% | 2 Nov → | ||
| 9–1 | 0.19 | 22% | 21 Oct → | ||
| 4–9 | -0.12 | 31% | 21 Oct → | ||
| 13–4 | -0.04 | 16% | 20 Oct → | ||
| 9–7 | 0.07 | 17% | 4 Oct → | ||
| 13–10 | -0.03 | 11% | 3 Oct → | ||
| 13–11 | -0.01 | 38% | 3 Oct → | ||
| 13–11 | -0.04 | 19% | 3 Oct → | ||
| 11–13 | -0.09 | 15% | 3 Oct → | ||
| italy | 6–13 | -0.11 | 19% | 3 Oct → | |
| 11–13 | -0.04 | 29% | 18 Sept → | ||
| 8–8 | -0.12 | 13% | 30 Aug → | ||
| 9–4 | -0.01 | 21% | 30 Aug → | ||
| mills | 10–13 | -0.07 | 17% | 24 Aug → | |
| assembly | 3–9 | -0.14 | 17% | 17 Aug → | |
| 11–13 | -0.07 | 13% | 10 Aug → | ||
| 4–13 | -0.10 | 17% | 5 Aug → | ||
| 3–9 | -0.24 | 9% | 5 Aug → | ||
| assembly | 5–9 | -0.08 | 19% | 5 Aug → | |
| 13–10 | -0.03 | 13% | 4 Aug → | ||
| 10–13 | -0.08 | 25% | 4 Aug → | ||
| 15–15 | -0.05 | 16% | 6 Jul → | ||
| memento | 2–9 | -0.19 | 10% | 29 Jun → | |
| office | 12–12 | -0.02 | 22% | 16 Jun → | |
| 13–8 | -0.03 | 14% | 16 Jun → | ||
| 13–8 | -0.00 | 18% | 31 May → | ||
| 10–13 | -0.11 | 15% | 4 May → | ||
| 13–10 | -0.01 | 24% | 4 May → | ||
| 13–10 | -0.09 | 21% | 1 May → | ||
| 5–13 | -0.06 | 31% | 1 May → | ||
| 7–13 | -0.10 | 22% | 27 Apr → | ||
| 13–16 | -0.09 | 15% | 26 Apr → | ||
| office | 8–13 | -0.00 | 10% | 22 Apr → | |
| 1–4 | -0.08 | 0% | 21 Apr → | ||
| 1–9 | -0.24 | 33% | 21 Apr → | ||
| 3–13 | -0.14 | 29% | 20 Apr → | ||
| 7–13 | -0.11 | 0% | 18 Apr → | ||
| 13–7 | -0.06 | 9% | 18 Apr → | ||
| 12–12 | -0.04 | 10% | 8 Apr → | ||
| 13–9 | -0.06 | 8% | 27 Mar → | ||
| 9–13 | -0.07 | 26% | 25 Mar → | ||
| 5–13 | -0.11 | 21% | 23 Mar → | ||
| 13–11 | -0.08 | 16% | 21 Mar → | ||
| 9–13 | -0.07 | 24% | 17 Mar → | ||
| 10–13 | -0.02 | 17% | 17 Mar → | ||
| 16–13 | -0.04 | 20% | 13 Mar → | ||
| 13–11 | -0.02 | 19% | 11 Mar → | ||
| 8–13 | -0.09 | 7% | 10 Mar → |
Match data via Leetify.