✞ -kaneko666- ✞ LFT — CS2 Stats
VN76561198987477422[U:1:1027211694]Steam profile ↗
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +0pp win rate · +0.00 avg rating
Player DNA
Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.
Sharp aimerStrong 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 NiKo 96% playstyle similarity
Most alike: aim profile, positioning 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
Aim. Aim score of 94 — the mechanical foundation is a clear strength.
Areas to improve
Positioning. Positioning trails aim by 34 points — deaths here waste a strong aim profile.
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
T-side openings. Opening success drops from 50% on CT to 26% on T — the same duels are being taken with worse setups on the attacking side.
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 7.7/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.05 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 |
|---|---|---|---|---|---|
 mirage | B | 32 | 15–17 | 47% | -0.00 |
 ancient | A | 20 | 11–9 | 55% | 0.02 |
 dust2 | B | 15 | 7–8 | 47% | 0.02 |
 anubis | C | 12 | 5–7 | 42% | -0.01 |
 nuke | C | 9 | 4–5 | 44% | -0.00 |
 overpass | S | 5 | 4–1 | 80% | 0.02 |
 inferno | — | 4 | 2–2 | 50% | 0.02 |
 train | — | 2 | 2–0 | 100% | -0.00 |
 cache | — | 1 | 0–1 | 0% | -0.00 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (42% over 12). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWWWWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 858 | 50% | 1.11 | 16.4 |
| Ancient | 836 | 52% | 1.22 | 17.9 |
| Anubis | 680 | 49% | 1.20 | 17.6 |
| Dust2 | 616 | 55% | 1.17 | 16.8 |
| Nuke | 281 | 56% | 1.17 | 17.4 |
| Vertigo | 199 | 55% | 1.29 | 18.3 |
| Inferno | 160 | 54% | 1.11 | 16.7 |
| Overpass | 127 | 53% | 1.22 | 17.5 |
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 26.1342% — 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.
42% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| ancient | 13–1 | 0.04 | 33% | 20 Aug → | |
| dust2 | 13–4 | -0.01 | 33% | 18 Aug → | |
| mirage | 13–10 | 0.00 | 24% | 16 Aug → | |
| nuke | 13–16 | -0.01 | 28% | 9 Aug → | |
| mirage | 10–13 | 0.02 | 19% | 12 Jul → | |
| anubis | 13–8 | -0.04 | 24% | 29 Jun → | |
| dust2 | 13–10 | -0.04 | 18% | 28 Jun → | |
| dust2 | 13–4 | 0.06 | 22% | 20 Jun → | |
| mirage | 8–13 | -0.03 | 48% | 19 Jun → | |
| anubis | 16–13 | 0.03 | 33% | 18 Jun → | |
| anubis | 11–13 | -0.03 | 29% | 14 Jun → | |
| mirage | 13–8 | -0.01 | 21% | 14 Jun → | |
| ancient | 13–4 | 0.06 | 32% | 13 Jun → | |
| anubis | 16–12 | 0.05 | 25% | 25 May → | |
| mirage | 16–13 | -0.00 | 38% | 22 May → | |
| dust2 | 13–7 | -0.05 | 62% | 19 May → | |
| ancient | 12–16 | -0.07 | 22% | 16 May → | |
| dust2 | 13–11 | 0.06 | 40% | 11 May → | |
| overpass | 13–2 | -0.01 | 25% | 8 May → | |
| ancient | 5–13 | -0.00 | 27% | 1 May → | |
| mirage | 9–13 | 0.06 | 29% | 28 Apr → | |
| nuke | 13–9 | 0.01 | 32% | 27 Apr → | |
| cache | 11–13 | -0.00 | 27% | 25 Apr → | |
| mirage | 10–13 | 0.05 | 21% | 25 Apr → | |
| mirage | 13–4 | 0.00 | 24% | 24 Apr → | |
| mirage | 13–8 | -0.04 | 33% | 23 Apr → | |
| mirage | 13–7 | -0.01 | 15% | 22 Apr → | |
| mirage | 13–10 | -0.04 | 30% | 22 Apr → | |
| dust2 | 13–7 | 0.21 | 51% | 21 Apr → | |
| dust2 | 3–13 | -0.01 | 38% | 21 Apr → | |
| mirage | 13–10 | -0.04 | 33% | 10 Apr → | |
| ancient | 10–13 | -0.00 | 45% | 8 Apr → | |
| anubis | 13–9 | -0.05 | 28% | 4 Apr → | |
| anubis | 6–13 | 0.00 | 19% | 4 Apr → | |
| nuke | 11–13 | -0.02 | 47% | 2 Apr → | |
| dust2 | 10–13 | -0.05 | 19% | 11 Mar → | |
| mirage | 6–13 | -0.09 | 26% | 25 Feb → | |
| mirage | 13–6 | 0.03 | 32% | 22 Feb → | |
| ancient | 13–4 | 0.11 | 28% | 17 Feb → | |
| dust2 | 13–6 | 0.12 | 38% | 17 Feb → | |
| inferno | 13–5 | 0.04 | 40% | 16 Feb → | |
| dust2 | 11–13 | 0.06 | 27% | 15 Feb → | |
| anubis | 5–13 | -0.00 | 23% | 11 Feb → | |
| mirage | 16–12 | 0.00 | 29% | 7 Feb → | |
| ancient | 13–4 | 0.06 | 23% | 5 Feb → | |
| ancient | 11–13 | -0.07 | 34% | 3 Feb → | |
| mirage | 10–13 | 0.02 | 32% | 3 Feb → | |
| nuke | 6–13 | -0.08 | 45% | 3 Feb → | |
| ancient | 13–6 | 0.06 | 32% | 3 Feb → | |
| inferno | 5–13 | 0.01 | 28% | 2 Feb → | |
| ancient | 4–13 | -0.04 | 32% | 1 Feb → | |
| ancient | 8–13 | -0.04 | 29% | 31 Jan → | |
| nuke | 13–8 | 0.05 | 21% | 30 Jan → | |
| ancient | 13–8 | -0.01 | 23% | 29 Jan → | |
| mirage | 9–13 | -0.07 | 21% | 26 Jan → | |
| anubis | 13–11 | -0.02 | 34% | 21 Jan → | |
| mirage | 10–13 | -0.02 | 18% | 21 Jan → | |
| anubis | 13–16 | 0.00 | 27% | 18 Jan → | |
| mirage | 4–13 | -0.05 | 18% | 16 Jan → | |
| train | 13–9 | 0.02 | 22% | 6 Jan → | |
| mirage | 13–11 | -0.02 | 22% | 2 Jan → | |
| mirage | 13–9 | 0.09 | 37% | 15 Dec → | |
| train | 13–10 | -0.02 | 29% | 14 Dec → | |
| mirage | 5–13 | -0.05 | 10% | 13 Dec → | |
| nuke | 11–13 | -0.01 | 30% | 9 Dec → | |
| dust2 | 8–13 | 0.03 | 38% | 27 Oct → | |
| ancient | 13–6 | 0.07 | 39% | 25 Oct → | |
| nuke | 13–8 | 0.01 | 24% | 25 Oct → | |
| mirage | 10–13 | -0.04 | 27% | 10 Oct → | |
| ancient | 13–5 | 0.07 | 33% | 29 Sept → | |
| ancient | 10–13 | -0.03 | 16% | 18 Sept → | |
| ancient | 7–13 | 0.01 | 28% | 18 Sept → | |
| dust2 | 10–13 | 0.04 | 22% | 23 Aug → | |
| mirage | 13–16 | -0.04 | 20% | 19 Aug → | |
| mirage | 13–5 | -0.03 | 17% | 15 Aug → | |
| mirage | 11–13 | 0.05 | 32% | 14 Aug → | |
| nuke | 13–5 | 0.05 | 23% | 14 Aug → | |
| ancient | 13–5 | 0.14 | 22% | 14 Aug → | |
| mirage | 13–10 | 0.03 | 28% | 9 Aug → | |
| overpass | 13–4 | 0.11 | 42% | 8 Aug → | |
| overpass | 13–6 | 0.02 | 24% | 5 Aug → | |
| mirage | 11–13 | 0.01 | 35% | 1 Aug → | |
| overpass | 13–5 | -0.04 | 23% | 30 Jul → | |
| mirage | 15–15 | 0.09 | 26% | 29 Jul → | |
| overpass | 12–12 | 0.04 | 28% | 29 Jul → | |
| mirage | 10–13 | -0.01 | 46% | 28 Jul → | |
| dust2 | 8–13 | -0.08 | 28% | 22 Jul → | |
| anubis | 9–13 | 0.01 | 21% | 14 Jul → | |
| ancient | 0–13 | -0.10 | 44% | 8 Jul → | |
| mirage | 13–8 | 0.01 | 30% | 30 Jun → | |
| dust2 | 10–13 | 0.06 | 40% | 29 Jun → | |
| inferno | 8–13 | -0.01 | 21% | 23 Jun → | |
| mirage | 11–13 | 0.01 | 44% | 22 Jun → | |
| ancient | 16–13 | 0.02 | 27% | 20 Jun → | |
| ancient | 13–7 | 0.04 | 29% | 19 Jun → | |
| anubis | 13–16 | -0.01 | 18% | 15 Jun → | |
| anubis | 8–13 | -0.00 | 36% | 13 Jun → | |
| dust2 | 3–13 | -0.06 | 36% | 11 Jun → | |
| nuke | 6–13 | -0.01 | 24% | 8 Jun → | |
| inferno | 13–8 | 0.06 | 30% | 5 Jun → |
Match data via Leetify.
