Handsome — CS2 Stats
76561199189907440[U:1:1229641712]Steam profile ↗✓ No bans
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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
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: 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 42% on CT to 23% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 619ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.
Counter-strafing. Only 69% 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 3.7/10 (Learning), 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 | 28 | 10–18 | 36% | -0.01 | |
| B | 20 | 10–10 | 50% | -0.02 | |
| B | 18 | 9–9 | 50% | -0.00 | |
| C | 14 | 6–8 | 43% | -0.01 | |
| D | 10 | 3–7 | 30% | -0.01 | |
| — | 4 | 3–1 | 75% | -0.00 | |
| — | 4 | 2–2 | 50% | 0.01 | |
| — | 1 | 0–1 | 0% | 0.00 | |
| — | 1 | 0–1 | 0% | -0.07 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (30% over 10). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsLWLWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Ancient | 7 | 29% | 0.64 | 11.6 |
| Anubis | 7 | 29% | 0.78 | 10.0 |
| Nuke | 6 | 33% | 0.84 | 13.0 |
| Mirage | 6 | 33% | 0.92 | 13.7 |
| Inferno | 6 | 50% | 0.85 | 11.5 |
| Dust2 | 1 | 0% | 0.88 | 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.
- 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 12.043% — below the 15% mark we flag
- 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 22.7752% — 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.
30% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–7 | -0.09 | 10% | 28 Aug → | ||
| 13–9 | 0.04 | 15% | 21 Aug → | ||
| 12–12 | 0.00 | 13% | 29 Jul → | ||
| 10–13 | 0.04 | 22% | 26 Jul → | ||
| 10–13 | 0.00 | 11% | 20 Jul → | ||
| 13–0 | 0.12 | 20% | 16 Jul → | ||
| 13–16 | -0.01 | 13% | 16 Jul → | ||
| 6–13 | 0.05 | 13% | 12 Jul → | ||
| 11–13 | -0.06 | 8% | 12 Jul → | ||
| 12–16 | -0.02 | 10% | 11 Jul → | ||
| 13–10 | 0.05 | 7% | 3 Jul → | ||
| 16–14 | 0.05 | 13% | 2 Jul → | ||
| 13–3 | -0.04 | 11% | 2 Jul → | ||
| 9–13 | -0.00 | 9% | 2 Jul → | ||
| 5–13 | -0.09 | 14% | 1 Jul → | ||
| 8–13 | -0.05 | 15% | 1 Jul → | ||
| 8–1 | 0.09 | 12% | 1 Jul → | ||
| 13–6 | -0.02 | 16% | 29 Jun → | ||
| 11–13 | -0.09 | 0% | 29 Jun → | ||
| 11–13 | 0.00 | 10% | 28 Jun → | ||
| 6–11 | 0.01 | 30% | 27 Jun → | ||
| 2–13 | -0.09 | 10% | 27 Jun → | ||
| 8–1 | 0.04 | 14% | 27 Jun → | ||
| 8–13 | -0.04 | 16% | 27 Jun → | ||
| 13–11 | 0.04 | 9% | 27 Jun → | ||
| 11–13 | -0.01 | 9% | 26 Jun → | ||
| 13–11 | 0.06 | 4% | 26 Jun → | ||
| 13–11 | -0.01 | 14% | 24 Jun → | ||
| 11–13 | -0.01 | 17% | 24 Jun → | ||
| 7–13 | 0.05 | 11% | 24 Jun → | ||
| 13–5 | 0.02 | 11% | 23 Jun → | ||
| 5–13 | 0.01 | 13% | 20 Jun → | ||
| 10–13 | 0.00 | 11% | 19 Jun → | ||
| 13–8 | -0.01 | 15% | 19 Jun → | ||
| 13–9 | 0.03 | 14% | 19 Jun → | ||
| 7–13 | 0.06 | 13% | 19 Jun → | ||
| 16–13 | 0.00 | 11% | 19 Jun → | ||
| 13–7 | 0.06 | 10% | 19 Jun → | ||
| 11–13 | -0.01 | 10% | 14 Jun → | ||
| 7–13 | 0.02 | 14% | 14 Jun → | ||
| 13–10 | 0.00 | 8% | 13 Jun → | ||
| 11–13 | -0.06 | 9% | 13 Jun → | ||
| 13–5 | -0.03 | 10% | 13 Jun → | ||
| 12–16 | -0.07 | 3% | 13 Jun → | ||
| 9–13 | -0.06 | 15% | 9 Jun → | ||
| 5–13 | -0.07 | 3% | 7 Jun → | ||
| 11–13 | 0.01 | 14% | 6 Jun → | ||
| 9–13 | -0.06 | 17% | 6 Jun → | ||
| 13–5 | -0.04 | 2% | 6 Jun → | ||
| 12–16 | -0.04 | 11% | 2 Jun → | ||
| 13–8 | 0.00 | 15% | 2 Jun → | ||
| 6–13 | -0.02 | 6% | 31 May → | ||
| 4–13 | -0.08 | 5% | 31 May → | ||
| 8–13 | 0.03 | 7% | 30 May → | ||
| 9–13 | -0.08 | 16% | 30 May → | ||
| 16–14 | -0.01 | 6% | 30 May → | ||
| 13–9 | -0.00 | 9% | 30 May → | ||
| 8–13 | -0.00 | 18% | 30 May → | ||
| 14–16 | -0.03 | 6% | 28 May → | ||
| 7–13 | -0.04 | 14% | 25 May → | ||
| 6–1 | 0.04 | 22% | 25 May → | ||
| 11–13 | -0.02 | 10% | 21 May → | ||
| 13–10 | -0.04 | 12% | 21 May → | ||
| 11–13 | -0.03 | 12% | 20 May → | ||
| 13–11 | -0.01 | 11% | 17 May → | ||
| 4–13 | 0.01 | 9% | 16 May → | ||
| 13–7 | 0.02 | 11% | 11 May → | ||
| 6–13 | -0.07 | 15% | 10 May → | ||
| 13–7 | -0.00 | 10% | 10 May → | ||
| 13–11 | -0.06 | 9% | 8 May → | ||
| 9–13 | -0.04 | 2% | 7 May → | ||
| 13–10 | 0.00 | 16% | 6 May → | ||
| 5–13 | -0.07 | 10% | 3 May → | ||
| 16–13 | 0.05 | 11% | 3 May → | ||
| 13–8 | 0.00 | 12% | 1 May → | ||
| 7–13 | -0.06 | 7% | 1 May → | ||
| 12–12 | -0.03 | 20% | 29 Apr → | ||
| 11–13 | -0.04 | 9% | 28 Apr → | ||
| 15–15 | 0.00 | 10% | 28 Apr → | ||
| 9–13 | 0.03 | 10% | 28 Apr → | ||
| 13–7 | 0.04 | 4% | 28 Apr → | ||
| 13–9 | -0.06 | 9% | 28 Apr → | ||
| 13–9 | -0.03 | 3% | 28 Apr → | ||
| 6–13 | -0.01 | 14% | 28 Apr → | ||
| 2–13 | -0.03 | 10% | 25 Apr → | ||
| 13–7 | -0.03 | 5% | 19 Apr → | ||
| 16–14 | 0.08 | 10% | 19 Apr → | ||
| 15–15 | -0.00 | 11% | 12 Apr → | ||
| 13–7 | 0.01 | 13% | 12 Apr → | ||
| 13–10 | -0.00 | 5% | 10 Apr → | ||
| 4–13 | -0.02 | 10% | 31 Mar → | ||
| 13–9 | -0.03 | 12% | 30 Mar → | ||
| 5–13 | -0.02 | 12% | 30 Mar → | ||
| 5–13 | 0.01 | 22% | 30 Mar → | ||
| 13–10 | -0.00 | 11% | 30 Mar → | ||
| 7–13 | -0.10 | 2% | 30 Mar → | ||
| 8–13 | 0.01 | 9% | 30 Mar → | ||
| 13–6 | 0.02 | 14% | 28 Mar → | ||
| 8–13 | -0.03 | 13% | 20 Mar → | ||
| 13–9 | 0.01 | 8% | 16 Mar → |
Match data via Leetify.