DUCK1E?♡™ — CS2 Stats
US76561199626959881[U:1:1666694153]Steam profile ↗
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +60pp win rate · +0.08 avg rating
Player DNA
Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.
Sharp aimerLimited 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 s1mple 90% playstyle similarity
Most alike: aim profile, opening-fight frequency.
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 98 — the mechanical foundation is a clear strength.
T openings. 67% T opening-duel success — entries that actually open the round.
Areas to improve
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
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 7.6/10 (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 | 20 | 17–3 | 85% | 0.08 | |
| S | 19 | 14–5 | 74% | 0.08 | |
| S | 16 | 13–3 | 81% | 0.09 | |
| S | 8 | 7–1 | 88% | 0.08 | |
| C | 8 | 3–5 | 38% | 0.06 | |
| S | 7 | 6–1 | 86% | 0.07 | |
| B | 6 | 3–3 | 50% | 0.05 | |
| C | 5 | 2–3 | 40% | 0.01 | |
| office | A | 5 | 3–2 | 60% | 0.02 |
| — | 4 | 4–0 | 100% | 0.14 | |
| — | 1 | 1–0 | 100% | 0.02 | |
| grail | — | 1 | 0–1 | 0% | 0.11 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (38% over 8). Start with the 6 essential Inferno 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 resultsWWWWW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 4 | 25% | 1.36 | 12.5 |
| Inferno | 3 | 100% | 1.13 | 12.0 |
| Nuke | 2 | 100% | 1.30 | 12.0 |
| Overpass | 1 | 0% | 0.36 | 5.0 |
| Anubis | 1 | 100% | 0.67 | 12.0 |
| Ancient | 1 | 100% | 0.36 | 5.0 |
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.
- 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 0.4291 — 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.
38% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–11 | 0.08 | 28% | 15 Aug → | ||
| 13–11 | 0.13 | 21% | 15 Aug → | ||
| 13–8 | 0.21 | 54% | 14 Aug → | ||
| 13–2 | 0.13 | 58% | 14 Aug → | ||
| 13–5 | 0.08 | 26% | 14 Aug → | ||
| 13–9 | 0.15 | 69% | 13 Aug → | ||
| 13–11 | 0.03 | 60% | 12 Aug → | ||
| 13–6 | 0.10 | 36% | 12 Aug → | ||
| 13–6 | 0.14 | 33% | 12 Aug → | ||
| 13–6 | 0.03 | 47% | 12 Aug → | ||
| 6–13 | 0.07 | 27% | 5 Aug → | ||
| 5–13 | -0.02 | 27% | 5 Aug → | ||
| 8–13 | -0.01 | 40% | 5 Aug → | ||
| 13–10 | -0.02 | 15% | 4 Aug → | ||
| 13–10 | 0.06 | 26% | 3 Aug → | ||
| 13–5 | 0.10 | 32% | 3 Aug → | ||
| 7–13 | -0.02 | 15% | 3 Aug → | ||
| 6–13 | -0.03 | 17% | 26 Jul → | ||
| 16–14 | 0.12 | 22% | 26 Jul → | ||
| 2–13 | -0.03 | 24% | 26 Jul → | ||
| 16–14 | 0.07 | 22% | 26 Jul → | ||
| 13–7 | 0.01 | 50% | 26 Jul → | ||
| 2–13 | -0.03 | 10% | 26 Jul → | ||
| 13–8 | 0.02 | 20% | 26 Jul → | ||
| 13–9 | 0.03 | 10% | 26 Jul → | ||
| 7–11 | 0.09 | 32% | 25 Jul → | ||
| 13–10 | 0.11 | 22% | 25 Jul → | ||
| 9–13 | -0.00 | 28% | 24 Jul → | ||
| 16–14 | 0.06 | 37% | 24 Jul → | ||
| 13–3 | 0.06 | 38% | 24 Jul → | ||
| 13–6 | 0.03 | 17% | 24 Jul → | ||
| 13–4 | 0.08 | 36% | 24 Jul → | ||
| 3–7 | 0.04 | 36% | 24 Jul → | ||
| 13–10 | 0.02 | 22% | 24 Jul → | ||
| 13–7 | -0.05 | 15% | 24 Jul → | ||
| 13–5 | 0.01 | 31% | 24 Jul → | ||
| 13–10 | 0.02 | 8% | 23 Jul → | ||
| 13–6 | 0.15 | 26% | 22 Jul → | ||
| 13–7 | 0.20 | 32% | 22 Jul → | ||
| 16–13 | 0.10 | 16% | 18 Dec → | ||
| 15–15 | 0.06 | 35% | 5 Dec → | ||
| 13–7 | 0.08 | 42% | 5 Dec → | ||
| 16–14 | 0.27 | 33% | 5 Dec → | ||
| 13–2 | 0.09 | 10% | 5 Dec → | ||
| 5–13 | 0.03 | 24% | 5 Dec → | ||
| 13–16 | 0.14 | 28% | 4 Dec → | ||
| 13–5 | 0.10 | 29% | 3 Dec → | ||
| 13–10 | 0.09 | 30% | 3 Dec → | ||
| 13–6 | 0.09 | 28% | 3 Dec → | ||
| 13–10 | 0.10 | 20% | 3 Dec → | ||
| 13–8 | 0.09 | 29% | 3 Dec → | ||
| 13–7 | 0.14 | 17% | 2 Dec → | ||
| 10–13 | 0.04 | 16% | 2 Dec → | ||
| 13–9 | 0.20 | 23% | 2 Dec → | ||
| 16–13 | 0.11 | 30% | 2 Dec → | ||
| 13–10 | 0.09 | 22% | 2 Dec → | ||
| 13–9 | 0.15 | 33% | 1 Dec → | ||
| 13–1 | 0.14 | 43% | 1 Dec → | ||
| 13–11 | 0.02 | 27% | 1 Dec → | ||
| 13–6 | 0.10 | 29% | 1 Dec → | ||
| 13–11 | -0.02 | 18% | 1 Dec → | ||
| 13–2 | 0.12 | 32% | 1 Dec → | ||
| 13–4 | 0.11 | 33% | 1 Dec → | ||
| 16–14 | 0.14 | 25% | 1 Dec → | ||
| 13–1 | 0.17 | 20% | 1 Dec → | ||
| office | 9–13 | -0.09 | 17% | 1 Dec → | |
| 13–6 | 0.04 | 28% | 1 Dec → | ||
| 13–4 | 0.06 | 26% | 1 Dec → | ||
| 13–5 | 0.14 | 38% | 1 Dec → | ||
| 13–0 | 0.11 | 17% | 30 Nov → | ||
| office | 5–13 | -0.06 | 20% | 30 Nov → | |
| office | 13–8 | 0.01 | 23% | 30 Nov → | |
| 13–4 | 0.25 | 56% | 26 May → | ||
| 12–12 | 0.00 | 0% | 26 May → | ||
| 5–1 | 0.10 | 65% | 25 May → | ||
| grail | 2–7 | 0.11 | 37% | 25 May → | |
| 13–10 | 0.05 | 58% | 25 May → | ||
| 10–13 | -0.06 | 42% | 24 May → | ||
| office | 13–1 | 0.07 | 47% | 23 May → | |
| office | 4–0 | 0.15 | 69% | 23 May → | |
| 13–3 | 0.12 | 36% | 23 May → | ||
| 8–13 | 0.10 | 36% | 22 May → | ||
| 16–14 | 0.03 | 46% | 1 Apr → | ||
| 13–2 | 0.20 | 90% | 1 Apr → | ||
| 13–9 | 0.05 | 51% | 1 Apr → | ||
| 7–6 | 0.11 | 50% | 1 Apr → | ||
| 13–8 | 0.11 | 60% | 1 Apr → | ||
| 13–16 | 0.08 | 33% | 1 Apr → | ||
| 6–2 | 0.07 | 89% | 29 Mar → | ||
| 10–13 | -0.05 | 27% | 29 Mar → | ||
| 6–13 | 0.07 | 24% | 29 Mar → | ||
| 5–13 | 0.02 | 23% | 29 Mar → | ||
| 16–12 | 0.03 | 25% | 27 Mar → | ||
| 13–7 | 0.07 | 53% | 26 Mar → | ||
| 10–1 | 0.22 | 76% | 25 Mar → | ||
| 15–15 | 0.09 | 75% | 25 Mar → | ||
| 15–15 | 0.09 | 27% | 25 Mar → | ||
| 3–13 | -0.03 | 36% | 23 Mar → | ||
| 13–5 | 0.05 | 24% | 23 Mar → | ||
| 13–10 | 0.07 | 31% | 22 Mar → |
Match data via Leetify.