Perp — CS2 Stats
76561198117341634[U:1:157075906]
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +40pp win rate · +0.01 avg rating
Player DNA
Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.
Excellent counter-strafingEffective flashes
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 88% playstyle similarity
Most alike: opening-fight frequency, utility contribution.
Where you differ: lower positioning profile; 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
Strengths
CT openings. 60% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
Flashes. 0.80 enemies blinded per flash — utility that consistently lands.
Areas to improve
Reaction time. 666ms 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 6.0/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.90 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 | 27 | 11–16 | 41% | 0.01 | |
| B | 20 | 9–11 | 45% | 0.00 | |
| B | 18 | 9–9 | 50% | 0.00 | |
| C | 13 | 5–8 | 38% | 0.01 | |
| D | 11 | 3–8 | 27% | -0.02 | |
| D | 5 | 1–4 | 20% | 0.02 | |
| — | 4 | 4–0 | 100% | 0.04 | |
| — | 1 | 1–0 | 100% | 0.11 | |
| — | 1 | 0–1 | 0% | -0.01 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsLWWWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Inferno | 19 | 53% | 1.04 | 14.2 |
| Vertigo | 16 | 75% | 1.33 | 16.4 |
| Mirage | 15 | 67% | 1.30 | 17.0 |
| Anubis | 14 | 50% | 1.09 | 15.3 |
| Ancient | 12 | 75% | 1.20 | 17.2 |
| Nuke | 10 | 50% | 2.24 | 18.3 |
| Dust2 | 7 | 57% | 1.05 | 14.3 |
| Overpass | 1 | 0% | 1.35 | 23.0 |
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
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 8–13 | -0.00 | 19% | 30 Jun → | ||
| 13–9 | 0.05 | 31% | 30 Jun → | ||
| 10–13 | -0.01 | 25% | 29 Jun → | ||
| 13–9 | 0.04 | 29% | 29 Jun → | ||
| 13–4 | 0.01 | 15% | 29 Jun → | ||
| 9–1 | -0.00 | 21% | 29 Jun → | ||
| 13–8 | 0.12 | 24% | 29 Jun → | ||
| 11–13 | 0.06 | 23% | 29 Jun → | ||
| 13–8 | 0.13 | 20% | 29 Jun → | ||
| 11–13 | 0.00 | 20% | 29 Jun → | ||
| 15–15 | 0.06 | 32% | 28 Jun → | ||
| 10–13 | 0.03 | 18% | 28 Jun → | ||
| 1–8 | 0.02 | 17% | 28 Jun → | ||
| 14–16 | -0.04 | 21% | 27 Jun → | ||
| 13–3 | 0.13 | 24% | 27 Jun → | ||
| 2–13 | -0.07 | 22% | 25 Jun → | ||
| 10–13 | 0.07 | 26% | 23 Jun → | ||
| 4–13 | -0.05 | 15% | 22 Jun → | ||
| 13–10 | 0.06 | 16% | 22 Jun → | ||
| 8–13 | 0.04 | 20% | 22 Jun → | ||
| 13–7 | 0.10 | 28% | 22 Jun → | ||
| 6–13 | 0.10 | 27% | 22 Jun → | ||
| 13–8 | 0.09 | 29% | 22 Jun → | ||
| 13–7 | 0.03 | 27% | 22 Jun → | ||
| 13–2 | 0.00 | 21% | 22 Jun → | ||
| 8–13 | -0.06 | 15% | 22 Jun → | ||
| 14–16 | 0.03 | 21% | 22 Jun → | ||
| 13–5 | 0.11 | 47% | 22 Jun → | ||
| 7–13 | -0.01 | 31% | 21 Jun → | ||
| 13–11 | 0.11 | 32% | 21 Jun → | ||
| 9–13 | 0.07 | 31% | 21 Jun → | ||
| 11–13 | 0.09 | 20% | 21 Jun → | ||
| 11–13 | -0.03 | 34% | 21 Jun → | ||
| 13–10 | -0.01 | 15% | 20 Jun → | ||
| 13–7 | 0.09 | 28% | 20 Jun → | ||
| 16–14 | -0.02 | 25% | 16 Jun → | ||
| 9–0 | 0.03 | 22% | 16 Jun → | ||
| 13–10 | 0.07 | 22% | 16 Jun → | ||
| 8–13 | 0.01 | 41% | 16 Jun → | ||
| 2–13 | -0.01 | 50% | 16 Jun → | ||
| 7–13 | -0.01 | 26% | 16 Jun → | ||
| 13–4 | 0.04 | 19% | 16 Jun → | ||
| 15–15 | -0.05 | 24% | 12 Jun → | ||
| 13–7 | 0.02 | 30% | 12 Jun → | ||
| 5–13 | -0.01 | 30% | 12 Jun → | ||
| 13–11 | 0.04 | 21% | 15 Feb → | ||
| 6–13 | -0.05 | 14% | 15 Feb → | ||
| 0–13 | -0.06 | 43% | 15 Feb → | ||
| 13–8 | 0.07 | 26% | 15 Feb → | ||
| 8–13 | -0.07 | 22% | 29 Aug → | ||
| 13–16 | -0.00 | 20% | 25 Apr → | ||
| 6–13 | -0.02 | 37% | 23 Apr → | ||
| 0–10 | -0.11 | 7% | 16 Apr → | ||
| 0–13 | -0.02 | 33% | 16 Apr → | ||
| 13–6 | -0.00 | 21% | 15 Apr → | ||
| 13–11 | 0.00 | 16% | 15 Apr → | ||
| 13–10 | -0.00 | 33% | 15 Apr → | ||
| 6–13 | -0.06 | 19% | 15 Apr → | ||
| 13–6 | 0.00 | 16% | 15 Apr → | ||
| 13–8 | -0.01 | 40% | 8 Apr → | ||
| 13–10 | -0.01 | 20% | 8 Apr → | ||
| 13–10 | 0.07 | 12% | 1 Apr → | ||
| 6–13 | -0.01 | 13% | 1 Apr → | ||
| 11–13 | 0.03 | 33% | 1 Apr → | ||
| 7–13 | 0.08 | 18% | 1 Apr → | ||
| 1–11 | -0.07 | 16% | 31 Mar → | ||
| 7–13 | -0.02 | 18% | 31 Mar → | ||
| 13–10 | -0.03 | 16% | 31 Mar → | ||
| 10–13 | -0.02 | 30% | 30 Mar → | ||
| 4–13 | 0.02 | 29% | 25 Mar → | ||
| 13–0 | 0.08 | 33% | 24 Mar → | ||
| 3–13 | -0.12 | 17% | 24 Mar → | ||
| 5–13 | 0.02 | 21% | 16 Mar → | ||
| 8–13 | -0.02 | 13% | 16 Mar → | ||
| 6–13 | -0.03 | 17% | 16 Mar → | ||
| 8–13 | -0.02 | 21% | 16 Mar → | ||
| 7–13 | 0.04 | 11% | 16 Mar → | ||
| 13–3 | 0.06 | 40% | 16 Mar → | ||
| 13–10 | 0.00 | 32% | 15 Mar → | ||
| 13–11 | -0.01 | 26% | 15 Mar → | ||
| 7–13 | 0.01 | 29% | 15 Mar → | ||
| 6–13 | -0.03 | 32% | 15 Mar → | ||
| 13–11 | -0.04 | 21% | 15 Mar → | ||
| 3–13 | -0.05 | 29% | 14 Mar → | ||
| 13–6 | 0.08 | 29% | 14 Mar → | ||
| 8–13 | -0.03 | 22% | 14 Mar → | ||
| 15–15 | 0.01 | 24% | 14 Mar → | ||
| 10–13 | -0.03 | 23% | 14 Mar → | ||
| 13–3 | 0.03 | 36% | 14 Mar → | ||
| 13–7 | -0.01 | 20% | 6 Mar → | ||
| 1–13 | -0.07 | 0% | 5 Mar → | ||
| 13–3 | -0.00 | 29% | 5 Mar → | ||
| 9–13 | -0.06 | 20% | 28 Feb → | ||
| 7–13 | -0.08 | 40% | 28 Feb → | ||
| 15–15 | -0.04 | 24% | 27 Feb → | ||
| 13–11 | -0.07 | 22% | 20 Feb → | ||
| 4–13 | -0.07 | 13% | 20 Feb → | ||
| 1–13 | -0.05 | 11% | 19 Feb → | ||
| 13–2 | 0.01 | 39% | 19 Feb → | ||
| 13–9 | -0.01 | 22% | 11 Feb → |
Match data via Leetify.