trale — CS2 Stats
76561198886785395[U:1:926519667]Steam profile ↗
How this compares with the same rank
Median values for Level 10 among CSDB-tracked players (n=3,007), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.
| Metric | This player | Level 10 median |
|---|---|---|
| Headshot rate | 67.3% | 52.0% |
| Shot accuracy | 6.3% | 13.7% |
| Kill/death ratio | 2.13 | 1.08 |
| Match win rate | 55.7% | 48.8% |
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +20pp 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-strafingStrong 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 Twistzz 95% playstyle similarity
Most alike: positioning profile, 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 90 — the mechanical foundation is a clear strength.
Areas to improve
Positioning. Positioning trails aim by 33 points — deaths here waste a strong aim profile.
T-side openings. Opening success drops from 58% on CT to 29% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 568ms 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 7.4/10 (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 |
|---|---|---|---|---|---|
| S | 32 | 21–11 | 66% | 0.04 | |
| A | 20 | 11–9 | 55% | 0.02 | |
| A | 19 | 11–8 | 58% | 0.01 | |
| A | 11 | 6–5 | 55% | 0.06 | |
| A | 7 | 4–3 | 57% | 0.05 | |
| D | 5 | 0–5 | 0% | 0.02 | |
| — | 2 | 2–0 | 100% | 0.08 | |
| — | 2 | 1–1 | 50% | 0.03 | |
| — | 1 | 0–1 | 0% | 0.06 | |
| — | 1 | 0–1 | 0% | 0.03 |
Across the last 100 tracked matches.
Nuke is currently your weakest sufficiently-sampled map (0% over 5). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.
Lifetime stats
Most-used weapons
Lifetime map wins
Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWWWLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 363 | 51% | 1.39 | 19.2 |
| Ancient | 234 | 58% | 1.42 | 18.6 |
| Dust2 | 201 | 48% | 1.38 | 18.3 |
| Anubis | 165 | 55% | 1.47 | 20.0 |
| Inferno | 124 | 56% | 1.47 | 20.6 |
| Nuke | 66 | 47% | 1.48 | 18.6 |
| Train | 14 | 36% | 1.45 | 19.2 |
| Overpass | 10 | 40% | 1.20 | 15.4 |
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 28.6493% — 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.
0% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 6–10 | -0.07 | 27% | 3 Aug → | ||
| 13–10 | -0.03 | 35% | 3 Aug → | ||
| 5–13 | -0.01 | 19% | 2 Aug → | ||
| 4–5 | -0.05 | 25% | 2 Aug → | ||
| 13–7 | 0.06 | 29% | 6 Jul → | ||
| 13–3 | 0.09 | 19% | 6 Jul → | ||
| 7–1 | 0.10 | 16% | 6 Jul → | ||
| 13–9 | 0.04 | 22% | 27 Jun → | ||
| 6–13 | 0.05 | 39% | 26 Jun → | ||
| 13–11 | 0.03 | 23% | 25 Jun → | ||
| 19–16 | 0.01 | 23% | 25 Jun → | ||
| 13–9 | 0.06 | 25% | 25 Jun → | ||
| 14–16 | 0.02 | 19% | 23 Jun → | ||
| 4–13 | 0.06 | 21% | 23 Jun → | ||
| 13–9 | -0.00 | 37% | 23 Jun → | ||
| 11–13 | -0.07 | 21% | 23 Jun → | ||
| 16–12 | 0.01 | 29% | 22 Jun → | ||
| 9–13 | -0.02 | 37% | 22 Jun → | ||
| 4–13 | -0.02 | 27% | 21 Jun → | ||
| 3–13 | -0.04 | 32% | 20 Jun → | ||
| 13–5 | 0.20 | 27% | 20 Jun → | ||
| 5–13 | 0.03 | 27% | 20 Jun → | ||
| 10–13 | 0.02 | 26% | 20 Jun → | ||
| 7–13 | 0.01 | 35% | 16 Jun → | ||
| 13–11 | 0.02 | 30% | 16 Jun → | ||
| 13–11 | 0.01 | 28% | 16 Jun → | ||
| 16–12 | 0.08 | 29% | 16 Jun → | ||
| 13–9 | 0.06 | 28% | 15 Jun → | ||
| 13–10 | 0.03 | 31% | 15 Jun → | ||
| 13–10 | 0.04 | 24% | 14 Jun → | ||
| 13–9 | 0.01 | 18% | 13 Jun → | ||
| 13–5 | 0.10 | 45% | 13 Jun → | ||
| 13–6 | 0.02 | 20% | 13 Jun → | ||
| 13–10 | 0.02 | 22% | 13 Jun → | ||
| 7–13 | -0.00 | 31% | 12 Jun → | ||
| 6–13 | 0.01 | 32% | 11 Jun → | ||
| 8–13 | 0.04 | 33% | 11 Jun → | ||
| 23–25 | -0.03 | 23% | 11 Jun → | ||
| 16–13 | 0.03 | 25% | 11 Jun → | ||
| 13–1 | 0.10 | 29% | 10 Jun → | ||
| 13–5 | 0.01 | 33% | 10 Jun → | ||
| 13–6 | 0.06 | 20% | 10 Jun → | ||
| 13–10 | 0.05 | 35% | 9 Jun → | ||
| 13–9 | 0.03 | 33% | 9 Jun → | ||
| 13–8 | 0.06 | 26% | 9 Jun → | ||
| 13–7 | -0.02 | 17% | 28 May → | ||
| 13–9 | 0.04 | 24% | 28 May → | ||
| 8–13 | 0.02 | 15% | 25 May → | ||
| 9–13 | -0.03 | 33% | 12 May → | ||
| 8–13 | 0.12 | 29% | 2 May → | ||
| 10–13 | 0.06 | 27% | 1 May → | ||
| 8–13 | 0.03 | 22% | 19 Apr → | ||
| 10–13 | 0.16 | 25% | 11 Apr → | ||
| 9–13 | 0.01 | 18% | 11 Apr → | ||
| 13–7 | 0.04 | 25% | 28 Mar → | ||
| 8–13 | -0.02 | 47% | 27 Mar → | ||
| 13–10 | 0.05 | 17% | 27 Mar → | ||
| 11–13 | -0.04 | 11% | 25 Mar → | ||
| 14–16 | -0.04 | 19% | 25 Mar → | ||
| 13–11 | 0.02 | 29% | 22 Mar → | ||
| 7–13 | 0.12 | 31% | 17 Mar → | ||
| 13–10 | 0.04 | 31% | 15 Mar → | ||
| 7–13 | 0.07 | 32% | 14 Mar → | ||
| 16–19 | 0.01 | 18% | 14 Mar → | ||
| 13–10 | 0.14 | 23% | 13 Mar → | ||
| 13–8 | 0.03 | 29% | 13 Mar → | ||
| 7–13 | -0.01 | 21% | 13 Mar → | ||
| 13–11 | 0.03 | 34% | 12 Mar → | ||
| 13–9 | 0.03 | 25% | 11 Mar → | ||
| 5–13 | -0.02 | 16% | 7 Mar → | ||
| 7–13 | 0.02 | 36% | 7 Mar → | ||
| 13–4 | 0.12 | 26% | 2 Mar → | ||
| 14–16 | 0.09 | 38% | 19 Feb → | ||
| 15–19 | -0.01 | 21% | 14 Feb → | ||
| 13–4 | -0.02 | 31% | 14 Feb → | ||
| 13–7 | -0.03 | 34% | 12 Feb → | ||
| 13–7 | -0.04 | 41% | 12 Feb → | ||
| 13–11 | 0.00 | 25% | 9 Feb → | ||
| 16–13 | 0.00 | 20% | 2 Feb → | ||
| 13–3 | -0.01 | 29% | 28 Jan → | ||
| 13–4 | 0.01 | 36% | 28 Jan → | ||
| 9–13 | 0.10 | 21% | 21 Jan → | ||
| 7–13 | 0.00 | 23% | 21 Jan → | ||
| 13–9 | 0.08 | 30% | 20 Jan → | ||
| 13–7 | 0.12 | 23% | 20 Jan → | ||
| 13–11 | 0.07 | 20% | 15 Jan → | ||
| 13–9 | 0.02 | 27% | 29 Dec → | ||
| 9–3 | 0.17 | 19% | 24 Dec → | ||
| 9–13 | 0.02 | 16% | 24 Dec → | ||
| 4–13 | 0.05 | 37% | 24 Dec → | ||
| 19–15 | 0.02 | 20% | 23 Dec → | ||
| 6–9 | 0.03 | 31% | 21 Dec → | ||
| 14–16 | 0.04 | 28% | 17 Dec → | ||
| 13–3 | 0.08 | 32% | 10 Dec → | ||
| 16–13 | -0.02 | 24% | 4 Dec → | ||
| 6–13 | -0.04 | 19% | 4 Dec → | ||
| 13–2 | 0.11 | 25% | 3 Dec → | ||
| 13–9 | 0.11 | 28% | 30 Nov → | ||
| 5–13 | -0.02 | 18% | 30 Nov → | ||
| 11–13 | 0.00 | 32% | 26 Nov → |
Match data via Leetify.