Malony — CS2 Stats
IM76561198178587065[U:1:218321337]Steam profile ↗✓ No bans
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +0pp win rate · +0.00 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
Sharp aimerStrong CT-side opener
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 91% playstyle similarity
Most alike: opening-fight frequency, positioning 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
Strengths
Aim. Aim score of 86 — the mechanical foundation is a clear strength.
CT openings. 66% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
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 66% on CT to 38% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 604ms 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 6.7/10 (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 |
|---|---|---|---|---|---|
| A | 22 | 12–10 | 55% | 0.03 | |
| A | 20 | 11–9 | 55% | 0.02 | |
| A | 18 | 11–7 | 61% | 0.05 | |
| A | 15 | 9–6 | 60% | 0.03 | |
| D | 10 | 3–7 | 30% | -0.00 | |
| — | 4 | 0–4 | 0% | -0.01 | |
| office | — | 3 | 0–3 | 0% | -0.01 |
| — | 3 | 1–2 | 33% | 0.07 | |
| — | 2 | 0–2 | 0% | 0.04 | |
| rooftop | — | 1 | 1–0 | 100% | 0.15 |
| dogtown | — | 1 | 1–0 | 100% | 0.07 |
| — | 1 | 0–1 | 0% | -0.02 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (30% over 10). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWLLLW
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 38.456% — 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.
30% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 9–13 | 0.03 | 31% | 18 Jul → | ||
| 15–15 | 0.04 | 21% | 18 Jul → | ||
| 7–13 | 0.07 | 22% | 7 Jun → | ||
| 13–4 | 0.14 | 26% | 7 Jun → | ||
| 13–11 | 0.01 | 28% | 7 Jun → | ||
| 12–12 | 0.06 | 28% | 31 May → | ||
| 13–7 | 0.04 | 24% | 31 May → | ||
| 13–4 | 0.22 | 44% | 31 May → | ||
| 9–13 | 0.03 | 25% | 22 May → | ||
| 10–13 | -0.02 | 17% | 22 May → | ||
| 11–13 | 0.03 | 26% | 13 May → | ||
| 11–13 | 0.09 | 29% | 13 May → | ||
| 3–13 | 0.05 | 29% | 13 May → | ||
| 7–13 | -0.01 | 43% | 13 May → | ||
| 2–13 | 0.06 | 60% | 13 May → | ||
| 13–8 | 0.03 | 29% | 13 May → | ||
| 13–5 | 0.08 | 50% | 12 May → | ||
| 13–7 | 0.05 | 12% | 11 May → | ||
| 11–13 | 0.00 | 18% | 11 May → | ||
| 13–2 | 0.20 | 28% | 8 May → | ||
| 13–1 | 0.10 | 27% | 8 May → | ||
| 13–10 | -0.05 | 35% | 8 May → | ||
| 13–7 | 0.11 | 26% | 8 May → | ||
| 13–16 | 0.08 | 22% | 8 May → | ||
| 6–13 | -0.06 | 43% | 8 May → | ||
| 13–9 | -0.01 | 43% | 8 May → | ||
| 5–13 | 0.02 | 45% | 6 May → | ||
| 2–7 | 0.01 | 23% | 6 May → | ||
| 13–11 | -0.01 | 27% | 6 May → | ||
| 13–4 | 0.10 | 27% | 6 May → | ||
| 11–13 | -0.04 | 24% | 6 May → | ||
| 9–13 | 0.02 | 33% | 5 May → | ||
| 7–13 | 0.00 | 24% | 5 May → | ||
| 13–5 | -0.00 | 36% | 5 May → | ||
| office | 11–13 | 0.00 | 56% | 1 May → | |
| 13–8 | 0.04 | 17% | 1 May → | ||
| 13–4 | 0.05 | 23% | 1 May → | ||
| 8–13 | -0.03 | 21% | 28 Dec → | ||
| 4–13 | 0.02 | 21% | 26 Dec → | ||
| 16–14 | -0.00 | 19% | 26 Dec → | ||
| 14–16 | 0.05 | 22% | 15 Dec → | ||
| 11–13 | -0.01 | 18% | 15 Dec → | ||
| 7–13 | -0.05 | 23% | 11 Dec → | ||
| 13–2 | -0.01 | 35% | 11 Dec → | ||
| 13–4 | 0.02 | 36% | 11 Dec → | ||
| 9–13 | -0.01 | 29% | 10 Dec → | ||
| 16–14 | -0.01 | 23% | 9 Dec → | ||
| 13–10 | 0.10 | 33% | 9 Dec → | ||
| 6–13 | -0.00 | 40% | 9 Dec → | ||
| rooftop | 9–5 | 0.15 | 18% | 8 Dec → | |
| 5–13 | -0.04 | 43% | 8 Dec → | ||
| 13–5 | 0.07 | 17% | 8 Dec → | ||
| 13–5 | 0.05 | 27% | 8 Dec → | ||
| 9–13 | -0.05 | 28% | 8 Dec → | ||
| 10–13 | 0.07 | 21% | 28 Nov → | ||
| 13–11 | 0.03 | 19% | 28 Nov → | ||
| 13–3 | 0.16 | 32% | 26 Nov → | ||
| 13–9 | 0.05 | 29% | 26 Nov → | ||
| 13–9 | -0.00 | 22% | 16 Nov → | ||
| 11–13 | -0.01 | 25% | 16 Nov → | ||
| 13–4 | 0.09 | 23% | 16 Nov → | ||
| 13–9 | 0.04 | 19% | 14 Nov → | ||
| 11–13 | -0.02 | 9% | 14 Nov → | ||
| 5–12 | 0.08 | 27% | 14 Nov → | ||
| 13–7 | 0.02 | 30% | 13 Nov → | ||
| 13–10 | 0.05 | 16% | 12 Nov → | ||
| 13–7 | -0.01 | 18% | 11 Nov → | ||
| 6–9 | 0.06 | 24% | 11 Nov → | ||
| 13–2 | 0.07 | 41% | 11 Nov → | ||
| 13–8 | 0.09 | 21% | 10 Nov → | ||
| 10–13 | -0.01 | 15% | 10 Nov → | ||
| 13–8 | -0.02 | 23% | 10 Nov → | ||
| 13–5 | 0.04 | 21% | 10 Nov → | ||
| 5–13 | -0.01 | 40% | 10 Nov → | ||
| 2–9 | -0.12 | 23% | 13 Sept → | ||
| 6–13 | 0.08 | 29% | 13 Sept → | ||
| 13–2 | 0.16 | 22% | 13 Sept → | ||
| 12–12 | -0.02 | 38% | 9 Sept → | ||
| dogtown | 9–6 | 0.07 | 24% | 9 Sept → | |
| 13–5 | 0.09 | 31% | 9 Sept → | ||
| 13–11 | -0.00 | 31% | 7 Sept → | ||
| 13–5 | 0.02 | 11% | 26 Aug → | ||
| 5–13 | 0.07 | 25% | 26 Aug → | ||
| 13–6 | 0.08 | 23% | 26 Aug → | ||
| 13–7 | 0.01 | 18% | 26 Aug → | ||
| 4–13 | -0.03 | 17% | 25 Aug → | ||
| 5–13 | -0.01 | 24% | 25 Aug → | ||
| 11–13 | 0.01 | 24% | 25 Aug → | ||
| 11–13 | -0.01 | 16% | 25 Aug → | ||
| office | 10–13 | 0.05 | 35% | 22 Aug → | |
| 13–2 | 0.10 | 33% | 22 Aug → | ||
| 2–11 | -0.02 | 25% | 21 Aug → | ||
| 8–13 | 0.03 | 15% | 21 Aug → | ||
| 9–13 | -0.03 | 6% | 21 Aug → | ||
| office | 4–13 | -0.07 | 46% | 15 Aug → | |
| 13–11 | 0.02 | 28% | 13 Aug → | ||
| 15–15 | -0.07 | 21% | 12 Aug → | ||
| 13–9 | 0.08 | 24% | 8 Aug → | ||
| 6–13 | -0.07 | 26% | 6 Aug → | ||
| 13–7 | 0.00 | 32% | 6 Aug → |
Match data via Leetify.