korigaboR 新 ドラゴン — CS2 Stats
76561198082018434[U:1:121752706]✓ No bans
How this compares with the same rank
Median values for Level 10 among CSDB-tracked players (n=218), 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 | 50.2% | 52.8% |
| Shot accuracy | 19.3% | 13.7% |
| Kill/death ratio | 1.22 | 1.08 |
| Match win rate | 48.3% | 49.2% |
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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
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
Sharp aimerEffective 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 b1t 96% playstyle similarity
Most alike: opening-fight frequency, 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 87 — the mechanical foundation is a clear strength.
Flashes. 0.76 enemies blinded per flash — utility that consistently lands.
Areas to improve
Reaction time. 595ms 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 6.5/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 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 |
|---|---|---|---|---|---|
| A | 23 | 14–9 | 61% | 0.04 | |
| D | 19 | 6–13 | 32% | 0.03 | |
| B | 17 | 9–8 | 53% | 0.05 | |
| B | 17 | 9–8 | 53% | 0.04 | |
| B | 15 | 7–8 | 47% | 0.02 | |
| — | 3 | 2–1 | 67% | 0.01 | |
| — | 2 | 1–1 | 50% | 0.04 | |
| — | 1 | 0–1 | 0% | -0.05 | |
| — | 1 | 0–1 | 0% | 0.03 | |
| alpine | — | 1 | 0–1 | 0% | 0.07 |
| office | — | 1 | 0–1 | 0% | -0.02 |
Across the last 100 tracked matches.
Dust 2 is currently your weakest sufficiently-sampled map (32% over 19). Start with the 6 essential Dust 2 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 resultsWWLWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Ancient | 6 | 67% | 2.09 | 20.3 |
| Dust2 | 6 | 83% | 1.44 | 15.7 |
| Inferno | 6 | 50% | 1.33 | 19.5 |
| Mirage | 6 | 50% | 1.56 | 22.0 |
| Train | 3 | 33% | 0.91 | 13.3 |
| Overpass | 1 | 0% | 1.29 | 18.0 |
| Anubis | 1 | 100% | 1.58 | 19.0 |
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.
32% win rate across 19 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 11–13 | 0.08 | 33% | 2 Apr → | ||
| 9–13 | 0.03 | 18% | 19 Mar → | ||
| 13–5 | 0.01 | 18% | 19 Mar → | ||
| 13–6 | 0.06 | 19% | 18 Mar → | ||
| 8–13 | 0.00 | 28% | 18 Mar → | ||
| 13–6 | 0.10 | 33% | 18 Mar → | ||
| 7–13 | -0.02 | 20% | 16 Mar → | ||
| 9–13 | -0.04 | 35% | 16 Mar → | ||
| 4–13 | 0.01 | 13% | 13 Mar → | ||
| 5–13 | -0.03 | 17% | 13 Mar → | ||
| 9–13 | 0.01 | 33% | 11 Mar → | ||
| 13–16 | 0.02 | 18% | 9 Mar → | ||
| 15–15 | 0.01 | 20% | 9 Mar → | ||
| 9–13 | -0.05 | 19% | 6 Mar → | ||
| 19–17 | 0.01 | 26% | 5 Mar → | ||
| 13–11 | 0.02 | 34% | 3 Mar → | ||
| 7–13 | 0.01 | 14% | 3 Mar → | ||
| 9–13 | 0.03 | 28% | 3 Mar → | ||
| 6–13 | 0.04 | 14% | 2 Mar → | ||
| 13–5 | 0.05 | 14% | 2 Mar → | ||
| 13–10 | 0.08 | 13% | 1 Mar → | ||
| 13–6 | -0.01 | 22% | 1 Mar → | ||
| 1–13 | -0.05 | 45% | 1 Mar → | ||
| 11–13 | 0.01 | 23% | 28 Feb → | ||
| 6–13 | 0.05 | 19% | 28 Feb → | ||
| 13–10 | 0.05 | 28% | 27 Feb → | ||
| 12–12 | -0.02 | 6% | 26 Feb → | ||
| 13–10 | 0.08 | 39% | 24 Feb → | ||
| 11–13 | 0.07 | 29% | 24 Feb → | ||
| 11–13 | 0.01 | 20% | 24 Feb → | ||
| 13–4 | 0.01 | 17% | 23 Feb → | ||
| 13–10 | 0.06 | 21% | 23 Feb → | ||
| 7–13 | 0.06 | 31% | 22 Feb → | ||
| 3–13 | 0.05 | 30% | 22 Feb → | ||
| 6–13 | -0.03 | 15% | 22 Feb → | ||
| 11–13 | 0.01 | 12% | 22 Feb → | ||
| 11–13 | 0.03 | 21% | 22 Feb → | ||
| 13–9 | 0.06 | 22% | 21 Feb → | ||
| 13–9 | 0.05 | 20% | 21 Feb → | ||
| 13–1 | 0.09 | 17% | 21 Feb → | ||
| 9–13 | -0.01 | 13% | 21 Feb → | ||
| 13–2 | 0.12 | 21% | 21 Feb → | ||
| 13–6 | 0.01 | 24% | 21 Feb → | ||
| 9–13 | -0.02 | 16% | 20 Feb → | ||
| 5–13 | 0.02 | 17% | 20 Feb → | ||
| 13–6 | 0.10 | 22% | 18 Feb → | ||
| 14–16 | 0.06 | 19% | 18 Feb → | ||
| 13–5 | 0.06 | 9% | 18 Feb → | ||
| 13–16 | -0.01 | 21% | 17 Feb → | ||
| 13–4 | 0.05 | 17% | 17 Feb → | ||
| 13–3 | 0.07 | 16% | 14 Feb → | ||
| 13–7 | 0.05 | 24% | 14 Feb → | ||
| 12–12 | 0.03 | 23% | 14 Feb → | ||
| 11–13 | -0.01 | 13% | 14 Feb → | ||
| 10–13 | 0.13 | 19% | 13 Feb → | ||
| 16–13 | 0.02 | 18% | 13 Feb → | ||
| 13–9 | 0.01 | 29% | 13 Feb → | ||
| 9–7 | 0.06 | 21% | 13 Feb → | ||
| 13–8 | -0.00 | 21% | 12 Feb → | ||
| 5–0 | 0.05 | 43% | 12 Feb → | ||
| 4–13 | -0.00 | 25% | 11 Feb → | ||
| alpine | 8–13 | 0.07 | 19% | 11 Feb → | |
| 16–13 | 0.03 | 16% | 11 Feb → | ||
| 13–10 | 0.05 | 15% | 10 Feb → | ||
| 13–8 | 0.09 | 20% | 10 Feb → | ||
| 10–13 | -0.03 | 18% | 10 Feb → | ||
| 13–11 | -0.01 | 24% | 9 Feb → | ||
| 10–13 | 0.05 | 16% | 9 Feb → | ||
| 7–13 | 0.11 | 29% | 8 Feb → | ||
| 13–5 | 0.12 | 25% | 8 Feb → | ||
| 12–16 | 0.03 | 15% | 6 Feb → | ||
| 13–4 | 0.02 | 27% | 6 Feb → | ||
| 13–7 | 0.08 | 20% | 5 Feb → | ||
| 13–7 | 0.11 | 23% | 5 Feb → | ||
| 13–6 | 0.10 | 30% | 4 Feb → | ||
| 9–13 | 0.05 | 37% | 4 Feb → | ||
| 9–2 | 0.10 | 29% | 3 Feb → | ||
| 13–7 | 0.06 | 24% | 3 Feb → | ||
| 8–13 | 0.00 | 26% | 3 Feb → | ||
| 13–6 | 0.00 | 25% | 3 Feb → | ||
| 11–13 | -0.02 | 16% | 3 Feb → | ||
| 15–15 | 0.03 | 22% | 2 Feb → | ||
| 13–7 | 0.05 | 36% | 1 Feb → | ||
| 13–7 | 0.01 | 20% | 1 Feb → | ||
| 10–13 | 0.13 | 24% | 1 Feb → | ||
| 13–11 | 0.06 | 31% | 31 Jan → | ||
| 5–13 | 0.01 | 22% | 31 Jan → | ||
| 11–13 | -0.04 | 14% | 31 Jan → | ||
| 13–3 | 0.06 | 12% | 31 Jan → | ||
| 13–7 | 0.05 | 27% | 31 Jan → | ||
| 7–13 | -0.02 | 25% | 31 Jan → | ||
| 0–11 | -0.02 | 100% | 30 Jan → | ||
| 11–13 | 0.03 | 19% | 30 Jan → | ||
| 14–16 | 0.02 | 14% | 29 Jan → | ||
| 7–13 | 0.02 | 19% | 29 Jan → | ||
| office | 9–13 | -0.02 | 33% | 29 Jan → | |
| 13–7 | 0.02 | 17% | 27 Jan → | ||
| 13–11 | 0.06 | 19% | 27 Jan → | ||
| 13–10 | 0.04 | 11% | 27 Jan → | ||
| 13–10 | 0.02 | 22% | 26 Jan → |
Match data via Leetify.