PuppyGirlAnya — CS2 Stats
76561199581303195[U:1:1621037467]
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +0pp win rate · +0.01 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 68% playstyle similarity
Most alike: opening-fight frequency, opening-duel success.
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
T-side openings. Opening success drops from 40% on CT to 24% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 641ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.
Counter-strafing. Only 64% 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 2.4/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.95 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 | 33 | 11–22 | 33% | -0.02 | |
| C | 22 | 8–14 | 36% | -0.03 | |
| C | 10 | 4–6 | 40% | -0.01 | |
| D | 10 | 2–8 | 20% | -0.01 | |
| D | 9 | 1–8 | 11% | -0.01 | |
| S | 6 | 5–1 | 83% | 0.02 | |
| D | 6 | 2–4 | 33% | -0.03 | |
| — | 2 | 0–2 | 0% | 0.02 | |
| italy | — | 1 | 1–0 | 100% | -0.01 |
| office | — | 1 | 0–1 | 0% | 0.08 |
Across the last 100 tracked matches.
Mirage is currently your weakest sufficiently-sampled map (11% over 9). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWLWWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 3 | 100% | 1.35 | 14.0 |
| Nuke | 1 | 0% | 0.89 | 16.0 |
| Dust2 | 1 | 100% | 1.00 | 15.0 |
| Anubis | 1 | 0% | 0.79 | 15.0 |
| Ancient | 1 | 100% | 0.84 | 16.0 |
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 12.0803° — 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 11.7501% — below the 15% 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 0.2778 — 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.
11% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 5–13 | -0.06 | 16% | 28 Aug → | ||
| 11–13 | 0.10 | 12% | 28 Aug → | ||
| 13–3 | 0.02 | 21% | 28 Aug → | ||
| 3–13 | -0.09 | 16% | 27 Aug → | ||
| 4–13 | -0.05 | 7% | 27 Aug → | ||
| 5–13 | -0.11 | 7% | 27 Aug → | ||
| 10–13 | -0.01 | 13% | 26 Aug → | ||
| 13–9 | 0.01 | 10% | 26 Aug → | ||
| 13–0 | 0.07 | 12% | 26 Aug → | ||
| 11–13 | -0.04 | 12% | 26 Aug → | ||
| 14–16 | -0.04 | 13% | 25 Aug → | ||
| 8–13 | -0.05 | 1% | 25 Aug → | ||
| 10–13 | -0.05 | 10% | 25 Aug → | ||
| 13–3 | -0.02 | 13% | 22 Aug → | ||
| 13–9 | 0.00 | 6% | 22 Aug → | ||
| 7–13 | -0.07 | 11% | 20 Aug → | ||
| 8–13 | -0.04 | 13% | 20 Aug → | ||
| 13–5 | 0.04 | 20% | 17 Aug → | ||
| 5–13 | 0.01 | 15% | 16 Aug → | ||
| 4–13 | -0.05 | 11% | 15 Aug → | ||
| 13–6 | 0.03 | 17% | 15 Aug → | ||
| 5–13 | -0.04 | 7% | 14 Aug → | ||
| 13–11 | 0.00 | 13% | 13 Aug → | ||
| 13–8 | -0.03 | 17% | 13 Aug → | ||
| 11–13 | 0.04 | 8% | 12 Aug → | ||
| 7–13 | -0.05 | 12% | 12 Aug → | ||
| 9–13 | -0.06 | 9% | 12 Aug → | ||
| 11–13 | -0.02 | 5% | 12 Aug → | ||
| 13–11 | -0.02 | 19% | 12 Aug → | ||
| 6–13 | 0.00 | 13% | 12 Aug → | ||
| 13–9 | 0.02 | 11% | 12 Aug → | ||
| 13–9 | 0.03 | 20% | 12 Aug → | ||
| 7–13 | -0.11 | 10% | 12 Aug → | ||
| 6–13 | -0.04 | 14% | 12 Aug → | ||
| 15–15 | -0.02 | 11% | 12 Aug → | ||
| 13–1 | 0.05 | 21% | 12 Aug → | ||
| 4–13 | -0.07 | 18% | 12 Aug → | ||
| 12–16 | -0.07 | 14% | 11 Aug → | ||
| 13–10 | -0.02 | 14% | 11 Aug → | ||
| 13–7 | 0.02 | 14% | 11 Aug → | ||
| 11–13 | -0.04 | 21% | 11 Aug → | ||
| 2–13 | -0.05 | 10% | 11 Aug → | ||
| 6–0 | 0.00 | 8% | 11 Aug → | ||
| 8–13 | 0.03 | 7% | 11 Aug → | ||
| 11–13 | -0.01 | 19% | 11 Aug → | ||
| 9–13 | -0.04 | 12% | 10 Aug → | ||
| 10–13 | -0.03 | 8% | 10 Aug → | ||
| 6–13 | -0.10 | 7% | 8 Aug → | ||
| 8–13 | -0.03 | 14% | 8 Aug → | ||
| 5–9 | 0.05 | 14% | 7 Aug → | ||
| 3–13 | -0.01 | 12% | 7 Aug → | ||
| 13–5 | -0.03 | 3% | 7 Aug → | ||
| 13–8 | 0.16 | 9% | 7 Aug → | ||
| 10–13 | -0.03 | 18% | 7 Aug → | ||
| 13–3 | -0.03 | 20% | 6 Aug → | ||
| 5–13 | -0.07 | 10% | 6 Aug → | ||
| 13–6 | -0.05 | 20% | 6 Aug → | ||
| 9–13 | -0.03 | 13% | 6 Aug → | ||
| 13–6 | 0.11 | 13% | 5 Aug → | ||
| 13–6 | 0.04 | 17% | 5 Aug → | ||
| 13–8 | 0.02 | 16% | 5 Aug → | ||
| 7–13 | -0.01 | 13% | 5 Aug → | ||
| 13–10 | 0.03 | 17% | 5 Aug → | ||
| 7–13 | 0.00 | 15% | 5 Aug → | ||
| 4–13 | -0.07 | 14% | 5 Aug → | ||
| 9–13 | -0.06 | 20% | 4 Aug → | ||
| 5–13 | -0.03 | 26% | 3 Aug → | ||
| 13–8 | -0.04 | 11% | 3 Aug → | ||
| 10–13 | 0.02 | 21% | 3 Aug → | ||
| 9–13 | -0.01 | 20% | 3 Aug → | ||
| 5–13 | -0.07 | 21% | 3 Aug → | ||
| 6–13 | -0.04 | 20% | 3 Aug → | ||
| 4–13 | 0.09 | 7% | 1 Aug → | ||
| 1–7 | -0.06 | 5% | 31 Jul → | ||
| 9–13 | -0.02 | 17% | 31 Jul → | ||
| 3–13 | -0.06 | 6% | 31 Jul → | ||
| 3–13 | -0.05 | 20% | 31 Jul → | ||
| 13–16 | 0.07 | 16% | 30 Jul → | ||
| 9–13 | 0.02 | 26% | 29 Jul → | ||
| 15–15 | -0.02 | 13% | 28 Jul → | ||
| 7–13 | -0.06 | 10% | 26 Jul → | ||
| italy | 13–7 | -0.01 | 21% | 26 Jul → | |
| 8–13 | -0.10 | 10% | 24 Jul → | ||
| 6–13 | -0.03 | 12% | 24 Jul → | ||
| 13–11 | -0.04 | 14% | 24 Jul → | ||
| 2–13 | -0.03 | 13% | 23 Jul → | ||
| 13–6 | 0.03 | 14% | 23 Jul → | ||
| 16–14 | -0.01 | 15% | 22 Jul → | ||
| 13–6 | 0.01 | 16% | 22 Jul → | ||
| 4–3 | -0.10 | 0% | 22 Jul → | ||
| 11–13 | 0.01 | 11% | 22 Jul → | ||
| 7–13 | -0.05 | 12% | 21 Jul → | ||
| 12–12 | -0.03 | 15% | 20 Jul → | ||
| 13–3 | -0.02 | 14% | 20 Jul → | ||
| 13–11 | 0.04 | 13% | 20 Jul → | ||
| 13–10 | -0.01 | 13% | 20 Jul → | ||
| 3–13 | -0.01 | 13% | 20 Jul → | ||
| office | 2–13 | 0.08 | 22% | 18 Jul → | |
| 7–13 | 0.01 | 19% | 18 Jul → | ||
| 7–13 | -0.01 | 12% | 17 Jul → |
Match data via Leetify.
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