moxx — CS2 Stats
76561198180639159[U:1:220373431]
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +0pp win rate · +0.02 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
Sharp aimerExcellent counter-strafingLimited 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 sh1ro 87% playstyle similarity
Most alike: opening-fight frequency, positioning profile.
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 88 — the mechanical foundation is a clear strength.
Counter-strafing. 92% of shots taken properly stopped — movement discipline most players never reach.
Areas to improve
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
Reaction time. 609ms 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 7.5/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.02 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 | 24 | 14–10 | 58% | 0.01 | |
| B | 23 | 12–11 | 52% | 0.02 | |
| S | 19 | 13–6 | 68% | 0.02 | |
| S | 12 | 9–3 | 75% | 0.03 | |
| D | 9 | 3–6 | 33% | -0.01 | |
| A | 5 | 3–2 | 60% | 0.00 | |
| — | 4 | 2–2 | 50% | 0.04 | |
| — | 2 | 0–2 | 0% | -0.02 | |
| — | 2 | 0–2 | 0% | -0.02 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWWLLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 610 | 56% | 1.16 | 18.2 |
| Dust2 | 460 | 54% | 1.16 | 18.4 |
| Ancient | 361 | 61% | 1.22 | 19.4 |
| Anubis | 163 | 54% | 1.19 | 18.6 |
| Train | 97 | 59% | 1.19 | 18.1 |
| Inferno | 49 | 55% | 1.24 | 18.6 |
| Overpass | 26 | 38% | 1.11 | 19.0 |
| Nuke | 10 | 40% | 0.93 | 14.1 |
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 0.4798 — 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.
33% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–5 | 0.20 | 35% | 16 May → | ||
| 13–8 | 0.03 | 19% | 6 May → | ||
| 13–3 | -0.04 | 33% | 23 Apr → | ||
| 13–16 | 0.04 | 32% | 21 Apr → | ||
| 11–13 | 0.07 | 24% | 21 Apr → | ||
| 13–9 | 0.08 | 27% | 28 Mar → | ||
| 8–13 | 0.05 | 21% | 14 Mar → | ||
| 13–9 | -0.03 | 14% | 9 Mar → | ||
| 13–9 | -0.04 | 26% | 9 Jan → | ||
| 7–13 | 0.01 | 16% | 4 Jan → | ||
| 16–12 | 0.09 | 25% | 31 Dec → | ||
| 13–3 | 0.04 | 27% | 27 Dec → | ||
| 13–5 | -0.05 | 30% | 23 Dec → | ||
| 10–13 | 0.01 | 28% | 16 Dec → | ||
| 13–5 | 0.06 | 37% | 22 Sept → | ||
| 11–13 | 0.02 | 21% | 22 Sept → | ||
| 13–4 | 0.01 | 38% | 29 Aug → | ||
| 13–10 | 0.07 | 26% | 13 Aug → | ||
| 6–13 | 0.02 | 39% | 1 Aug → | ||
| 6–13 | -0.08 | 32% | 31 Jul → | ||
| 13–8 | 0.04 | 25% | 27 Jul → | ||
| 7–13 | -0.03 | 14% | 29 Jun → | ||
| 13–9 | -0.02 | 28% | 28 Jun → | ||
| 13–2 | 0.05 | 28% | 30 May → | ||
| 1–6 | 0.01 | 18% | 30 May → | ||
| 13–7 | 0.13 | 38% | 28 May → | ||
| 13–8 | 0.06 | 21% | 16 May → | ||
| 13–10 | 0.01 | 24% | 16 May → | ||
| 13–6 | 0.03 | 19% | 11 May → | ||
| 13–9 | 0.06 | 31% | 10 May → | ||
| 16–14 | 0.03 | 28% | 10 May → | ||
| 6–13 | -0.03 | 24% | 10 May → | ||
| 13–4 | 0.13 | 39% | 10 Apr → | ||
| 10–13 | -0.03 | 15% | 11 Mar → | ||
| 13–5 | 0.11 | 35% | 10 Mar → | ||
| 9–13 | -0.03 | 21% | 28 Feb → | ||
| 13–11 | -0.02 | 18% | 28 Feb → | ||
| 5–13 | -0.02 | 24% | 22 Feb → | ||
| 13–10 | 0.04 | 21% | 25 Jan → | ||
| 13–11 | -0.02 | 23% | 22 Jan → | ||
| 13–9 | 0.05 | 31% | 22 Jan → | ||
| 13–2 | -0.04 | 31% | 21 Jan → | ||
| 10–13 | -0.01 | 34% | 21 Jan → | ||
| 13–6 | 0.04 | 33% | 17 Jan → | ||
| 11–13 | 0.06 | 31% | 5 Jan → | ||
| 8–13 | -0.03 | 15% | 29 Dec → | ||
| 10–13 | -0.05 | 17% | 29 Dec → | ||
| 13–8 | 0.03 | 33% | 28 Dec → | ||
| 11–13 | -0.05 | 15% | 26 Dec → | ||
| 13–10 | 0.00 | 30% | 14 Dec → | ||
| 9–13 | -0.03 | 32% | 13 Dec → | ||
| 7–13 | -0.06 | 18% | 10 Dec → | ||
| 14–16 | 0.03 | 40% | 9 Dec → | ||
| 13–5 | 0.15 | 25% | 25 Nov → | ||
| 13–11 | 0.01 | 31% | 14 Nov → | ||
| 13–7 | -0.00 | 28% | 12 Nov → | ||
| 13–1 | 0.20 | 37% | 11 Nov → | ||
| 11–13 | 0.02 | 35% | 10 Nov → | ||
| 13–8 | 0.01 | 32% | 14 Jan → | ||
| 2–13 | -0.11 | 11% | 16 Nov → | ||
| 16–3 | 0.06 | 33% | 6 Jul → | ||
| 14–16 | -0.02 | 25% | 25 Mar → | ||
| 16–4 | 0.02 | 23% | 25 Mar → | ||
| 10–16 | -0.03 | 39% | 4 Mar → | ||
| 14–16 | 0.04 | 22% | 13 Feb → | ||
| 17–19 | -0.03 | 38% | 18 Jan → | ||
| 19–16 | -0.03 | 15% | 18 Jan → | ||
| 16–12 | -0.02 | 24% | 10 Jan → | ||
| 12–16 | 0.00 | 20% | 8 Jan → | ||
| 13–16 | -0.06 | 22% | 7 Jan → | ||
| 10–16 | -0.06 | 18% | 4 Jan → | ||
| 4–16 | -0.05 | 20% | 31 Dec → | ||
| 16–7 | 0.01 | 21% | 30 Dec → | ||
| 16–13 | 0.01 | 33% | 29 Dec → | ||
| 16–5 | 0.06 | 28% | 28 Dec → | ||
| 14–16 | -0.04 | 15% | 19 Dec → | ||
| 9–16 | -0.02 | 22% | 10 Dec → | ||
| 15–15 | 0.10 | 26% | 3 Dec → | ||
| 16–10 | -0.06 | 35% | 1 Dec → | ||
| 16–13 | -0.01 | 26% | 5 Nov → | ||
| 16–4 | 0.13 | 27% | 22 Oct → | ||
| 8–16 | -0.06 | 31% | 17 Oct → | ||
| 12–16 | -0.01 | 18% | 4 Sept → | ||
| 16–11 | 0.02 | 22% | 4 Sept → | ||
| 16–7 | 0.06 | 24% | 18 Aug → | ||
| 16–7 | 0.07 | 29% | 14 Aug → | ||
| 10–16 | -0.09 | 26% | 31 Jul → | ||
| 10–16 | -0.02 | 29% | 31 Jul → | ||
| 16–4 | 0.11 | 26% | 31 Jul → | ||
| 10–16 | 0.04 | 33% | 9 Jun → | ||
| 16–10 | 0.08 | 34% | 15 May → | ||
| 3–16 | -0.05 | 26% | 5 Apr → | ||
| 15–15 | 0.08 | 35% | 19 Mar → | ||
| 16–10 | 0.07 | 24% | 24 Feb → | ||
| 5–16 | 0.02 | 35% | 20 Feb → | ||
| 15–19 | 0.00 | 14% | 6 Feb → | ||
| 19–17 | 0.00 | 30% | 4 Feb → | ||
| 16–11 | 0.03 | 16% | 3 Feb → | ||
| 19–17 | 0.02 | 19% | 3 Feb → | ||
| 16–14 | 0.05 | 24% | 3 Feb → |
Match data via Leetify.
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