moosenaround — CS2 Stats
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -10pp win rate · -0.03 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 80% playstyle similarity
Most alike: utility contribution, opening-fight frequency.
Where you differ: lower opening-duel success; 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
T-side openings. Opening success drops from 36% on CT to 21% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 567ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.
Counter-strafing. Only 70% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.
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 4.6/10 (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 |
|---|---|---|---|---|---|
| C | 16 | 7–9 | 44% | -0.03 | |
| C | 14 | 6–8 | 43% | -0.01 | |
| A | 12 | 7–5 | 58% | -0.02 | |
| C | 9 | 4–5 | 44% | -0.02 | |
| C | 9 | 4–5 | 44% | -0.02 | |
| B | 8 | 4–4 | 50% | -0.04 | |
| D | 8 | 1–7 | 13% | -0.03 | |
| C | 8 | 3–5 | 38% | -0.00 | |
| S | 7 | 6–1 | 86% | -0.03 | |
| D | 6 | 2–4 | 33% | -0.00 | |
| warden | — | 1 | 1–0 | 100% | 0.01 |
| office | — | 1 | 0–1 | 0% | -0.00 |
| golden | — | 1 | 1–0 | 100% | 0.04 |
Across the last 100 tracked matches.
Dust 2 is currently your weakest sufficiently-sampled map (13% over 8). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWLLWW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Dust2 | 12 | 67% | 1.31 | 17.8 |
| Anubis | 11 | 64% | 1.02 | 15.8 |
| Mirage | 9 | 67% | 0.89 | 13.9 |
| Inferno | 8 | 75% | 1.02 | 15.9 |
| Ancient | 5 | 40% | 1.09 | 16.2 |
| Cache | 4 | 75% | 0.96 | 12.8 |
| Train | 3 | 67% | 0.94 | 17.7 |
| Nuke | 2 | 50% | 1.13 | 15.0 |
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 12.0745° — above the 12° mark we flag
- Best CS2 CrosshairAim Training →
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 13.1407% — below the 15% mark we flag
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
13% 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 | -0.04 | 12% | 28 Aug → | ||
| 11–13 | -0.05 | 11% | 28 Aug → | ||
| 10–13 | -0.05 | 24% | 28 Aug → | ||
| 13–6 | -0.01 | 17% | 27 Aug → | ||
| 13–10 | -0.06 | 9% | 27 Aug → | ||
| 13–0 | -0.06 | 14% | 27 Aug → | ||
| 9–13 | 0.01 | 13% | 24 Aug → | ||
| 9–13 | -0.03 | 11% | 24 Aug → | ||
| 5–13 | -0.07 | 15% | 24 Aug → | ||
| 5–13 | -0.03 | 18% | 20 Aug → | ||
| 13–10 | -0.04 | 7% | 20 Aug → | ||
| 15–15 | -0.06 | 10% | 19 Aug → | ||
| 9–13 | -0.01 | 15% | 18 Aug → | ||
| 13–11 | -0.05 | 14% | 18 Aug → | ||
| 6–13 | 0.02 | 11% | 17 Aug → | ||
| 4–13 | 0.02 | 15% | 17 Aug → | ||
| 7–13 | -0.05 | 4% | 16 Aug → | ||
| 6–2 | -0.00 | 45% | 16 Aug → | ||
| 13–8 | 0.05 | 20% | 16 Aug → | ||
| 9–2 | 0.00 | 11% | 15 Aug → | ||
| 13–6 | -0.00 | 26% | 15 Aug → | ||
| 13–2 | 0.05 | 7% | 15 Aug → | ||
| 13–9 | -0.06 | 8% | 14 Aug → | ||
| 13–6 | -0.00 | 5% | 14 Aug → | ||
| 13–5 | -0.03 | 20% | 14 Aug → | ||
| 9–13 | -0.04 | 18% | 6 Aug → | ||
| 13–7 | -0.03 | 6% | 6 Aug → | ||
| 12–12 | -0.02 | 14% | 4 Aug → | ||
| 12–12 | -0.02 | 10% | 4 Aug → | ||
| 8–13 | 0.08 | 6% | 3 Aug → | ||
| 13–5 | 0.02 | 32% | 17 Jul → | ||
| 9–13 | 0.02 | 14% | 16 Jul → | ||
| 3–13 | -0.05 | 9% | 16 Jul → | ||
| 5–13 | -0.02 | 18% | 14 Jul → | ||
| 13–11 | -0.01 | 15% | 13 Jul → | ||
| 7–13 | -0.06 | 8% | 13 Jul → | ||
| 13–8 | -0.03 | 7% | 10 Jul → | ||
| 3–13 | -0.05 | 17% | 7 Jul → | ||
| 12–12 | 0.08 | 13% | 2 Jul → | ||
| 3–13 | -0.02 | 11% | 2 Jul → | ||
| 14–16 | -0.04 | 13% | 1 Jul → | ||
| warden | 13–1 | 0.01 | 20% | 1 Jul → | |
| 25–22 | -0.01 | 19% | 30 Jun → | ||
| 7–13 | -0.03 | 13% | 2 Jun → | ||
| 13–7 | -0.06 | 16% | 1 May → | ||
| 12–12 | 0.00 | 15% | 29 Apr → | ||
| 8–13 | -0.05 | 8% | 29 Apr → | ||
| 12–12 | 0.02 | 13% | 19 Mar → | ||
| 6–13 | -0.03 | 12% | 19 Mar → | ||
| 9–13 | 0.03 | 20% | 19 Mar → | ||
| 7–13 | -0.04 | 10% | 4 Mar → | ||
| 7–13 | -0.03 | 9% | 4 Mar → | ||
| 16–14 | 0.02 | 13% | 2 Feb → | ||
| 13–8 | -0.06 | 16% | 2 Feb → | ||
| 13–11 | -0.03 | 15% | 28 Jan → | ||
| 14–16 | -0.05 | 10% | 23 Jan → | ||
| 13–9 | -0.08 | 12% | 23 Jan → | ||
| 13–10 | -0.03 | 10% | 17 Jan → | ||
| 13–9 | 0.01 | 11% | 17 Jan → | ||
| 13–8 | -0.03 | 16% | 17 Jan → | ||
| 13–5 | -0.01 | 13% | 14 Jan → | ||
| 13–9 | -0.06 | 17% | 14 Jan → | ||
| 10–13 | -0.06 | 7% | 10 Jan → | ||
| 13–7 | -0.04 | 10% | 10 Jan → | ||
| 13–6 | 0.01 | 25% | 6 Jan → | ||
| 13–9 | -0.00 | 20% | 3 Jan → | ||
| 7–13 | -0.02 | 11% | 3 Jan → | ||
| 12–12 | 0.09 | 19% | 3 Jan → | ||
| 4–13 | -0.12 | 13% | 24 Dec → | ||
| 9–13 | -0.01 | 22% | 23 Dec → | ||
| 13–7 | -0.03 | 8% | 23 Dec → | ||
| 13–7 | 0.02 | 11% | 23 Dec → | ||
| 13–11 | -0.07 | 11% | 20 Dec → | ||
| 13–5 | -0.03 | 13% | 20 Dec → | ||
| 13–10 | -0.03 | 12% | 17 Dec → | ||
| 15–15 | -0.07 | 8% | 16 Dec → | ||
| 13–5 | -0.00 | 12% | 15 Dec → | ||
| 10–13 | 0.05 | 9% | 15 Dec → | ||
| 15–15 | -0.05 | 17% | 9 Dec → | ||
| 4–13 | 0.00 | 11% | 8 Dec → | ||
| office | 12–12 | -0.00 | 15% | 2 Dec → | |
| 11–13 | 0.03 | 15% | 27 Nov → | ||
| 10–13 | 0.01 | 15% | 25 Nov → | ||
| 13–4 | 0.02 | 6% | 25 Nov → | ||
| 13–10 | -0.01 | 18% | 24 Nov → | ||
| 6–13 | -0.04 | 14% | 24 Nov → | ||
| golden | 13–7 | 0.04 | 19% | 24 Nov → | |
| 13–16 | -0.02 | 19% | 20 Nov → | ||
| 6–13 | -0.04 | 15% | 20 Nov → | ||
| 10–13 | -0.03 | 24% | 18 Nov → | ||
| 13–2 | -0.03 | 4% | 7 Nov → | ||
| 12–12 | -0.06 | 11% | 6 Nov → | ||
| 4–13 | -0.00 | 15% | 6 Nov → | ||
| 3–13 | -0.00 | 24% | 6 Nov → | ||
| 6–13 | -0.03 | 13% | 6 Nov → | ||
| 5–13 | -0.06 | 9% | 23 Oct → | ||
| 10–13 | -0.00 | 11% | 23 Oct → | ||
| 13–11 | -0.05 | 9% | 16 Oct → | ||
| 13–8 | -0.02 | 12% | 9 Oct → | ||
| 13–2 | 0.00 | 17% | 4 Oct → |
Match data via Leetify.