nohrling — CS2 Stats
76561198945828320[U:1:985562592]✓ No bans
How this compares with the same rank
Median values for Level 10 among CSDB-tracked players (n=4,917), 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 | 54.4% | 51.9% |
| Shot accuracy | 12.5% | 13.7% |
| Kill/death ratio | 1.06 | 1.08 |
| Match win rate | 49.0% | 48.7% |
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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: Entry Fragger — High opening-fight frequency with above-par success in them.
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 s1mple 96% playstyle similarity
Most alike: opening-fight frequency, 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 88 — the mechanical foundation is a clear strength.
CT openings. 67% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
Areas to improve
T-side openings. Opening success drops from 67% on CT to 52% 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 7.8/10 (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 |
|---|---|---|---|---|---|
 nuke | B | 19 | 9–10 | 47% | 0.09 |
 mirage | B | 16 | 8–8 | 50% | 0.06 |
 dust2 | B | 16 | 8–8 | 50% | 0.04 |
 ancient | D | 14 | 4–10 | 29% | 0.05 |
 inferno | B | 8 | 4–4 | 50% | 0.05 |
 anubis | A | 7 | 4–3 | 57% | 0.09 |
 train | D | 6 | 1–5 | 17% | 0.08 |
 cache | D | 5 | 1–4 | 20% | 0.06 |
 overpass | A | 5 | 3–2 | 60% | 0.06 |
 vertigo | — | 3 | 2–1 | 67% | 0.10 |
| office | — | 1 | 1–0 | 100% | 0.11 |
Across the last 100 tracked matches.
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 resultsWLWLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Ancient | 168 | 55% | 1.13 | 17.5 |
| Mirage | 117 | 38% | 1.07 | 16.7 |
| Nuke | 94 | 61% | 1.24 | 17.8 |
| Inferno | 76 | 55% | 1.13 | 15.9 |
| Anubis | 74 | 53% | 1.25 | 17.9 |
| Dust2 | 64 | 48% | 1.11 | 17.9 |
| Overpass | 49 | 59% | 1.20 | 18.2 |
| Train | 41 | 59% | 1.27 | 19.5 |
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
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| nuke | 7–13 | 0.13 | 24% | 15 Aug → | |
| train | 13–3 | 0.03 | 42% | 15 Aug → | |
| cache | 11–13 | 0.10 | 31% | 28 Jul → | |
| anubis | 12–12 | 0.17 | 27% | 27 Jul → | |
| vertigo | 13–10 | 0.11 | 24% | 27 Jul → | |
| ancient | 5–13 | -0.10 | 13% | 27 Jul → | |
| mirage | 13–9 | 0.08 | 16% | 20 Jul → | |
| ancient | 2–13 | 0.06 | 22% | 18 Jul → | |
| anubis | 13–11 | 0.04 | 19% | 14 Jul → | |
| train | 12–12 | 0.04 | 20% | 6 Jul → | |
| dust2 | 13–2 | 0.18 | 24% | 6 Jul → | |
| office | 13–11 | 0.11 | 18% | 5 Jul → | |
| dust2 | 13–9 | -0.03 | 17% | 30 Jun → | |
| anubis | 13–7 | 0.12 | 34% | 28 Jun → | |
| inferno | 13–11 | 0.12 | 26% | 25 Jun → | |
| nuke | 7–13 | -0.06 | 17% | 25 Jun → | |
| dust2 | 9–13 | 0.07 | 17% | 23 Jun → | |
| mirage | 13–8 | 0.17 | 33% | 23 Jun → | |
| nuke | 9–13 | 0.06 | 28% | 17 Jun → | |
| train | 12–12 | 0.12 | 23% | 17 Jun → | |
| train | 11–13 | 0.09 | 24% | 16 Jun → | |
| cache | 10–13 | 0.07 | 23% | 9 Jun → | |
| cache | 7–13 | 0.05 | 24% | 4 Jun → | |
| overpass | 13–1 | 0.07 | 15% | 29 May → | |
| train | 12–12 | 0.01 | 17% | 20 May → | |
| dust2 | 13–5 | 0.09 | 32% | 14 May → | |
| nuke | 13–5 | 0.06 | 30% | 13 May → | |
| mirage | 13–8 | 0.12 | 28% | 13 May → | |
| cache | 13–9 | 0.11 | 20% | 10 May → | |
| ancient | 9–13 | -0.02 | 27% | 6 May → | |
| cache | 4–13 | -0.01 | 31% | 3 May → | |
| mirage | 10–13 | -0.08 | 16% | 23 Apr → | |
| mirage | 13–6 | 0.15 | 20% | 20 Apr → | |
| nuke | 8–13 | 0.09 | 17% | 19 Apr → | |
| nuke | 13–8 | 0.22 | 37% | 16 Apr → | |
| nuke | 10–13 | 0.00 | 20% | 12 Apr → | |
| ancient | 13–5 | 0.11 | 23% | 12 Apr → | |
| nuke | 13–6 | 0.11 | 28% | 11 Apr → | |
| ancient | 12–12 | 0.15 | 19% | 8 Apr → | |
| nuke | 7–13 | 0.05 | 21% | 7 Apr → | |
| nuke | 13–11 | 0.02 | 10% | 4 Apr → | |
| anubis | 13–11 | 0.05 | 31% | 2 Apr → | |
| ancient | 13–8 | -0.01 | 25% | 2 Apr → | |
| ancient | 13–8 | -0.02 | 13% | 2 Apr → | |
| overpass | 13–5 | 0.07 | 21% | 31 Mar → | |
| dust2 | 13–11 | 0.07 | 30% | 25 Mar → | |
| mirage | 1–13 | 0.03 | 26% | 19 Mar → | |
| nuke | 11–13 | 0.11 | 25% | 18 Mar → | |
| inferno | 0–5 | -0.02 | 40% | 11 Mar → | |
| inferno | 2–13 | 0.06 | 11% | 10 Mar → | |
| nuke | 8–13 | 0.18 | 30% | 8 Mar → | |
| inferno | 13–6 | 0.09 | 21% | 7 Mar → | |
| overpass | 3–7 | 0.05 | 50% | 6 Mar → | |
| ancient | 9–13 | 0.01 | 22% | 5 Mar → | |
| mirage | 13–6 | 0.08 | 13% | 4 Mar → | |
| inferno | 13–10 | -0.01 | 12% | 3 Mar → | |
| dust2 | 13–10 | 0.10 | 22% | 3 Mar → | |
| ancient | 11–13 | 0.03 | 20% | 3 Mar → | |
| nuke | 13–5 | 0.14 | 35% | 2 Mar → | |
| mirage | 13–3 | 0.09 | 26% | 2 Mar → | |
| dust2 | 1–13 | -0.01 | 19% | 1 Mar → | |
| dust2 | 2–13 | -0.08 | 44% | 26 Feb → | |
| mirage | 13–10 | 0.04 | 21% | 24 Feb → | |
| ancient | 3–13 | 0.03 | 35% | 23 Feb → | |
| dust2 | 15–15 | 0.07 | 22% | 22 Feb → | |
| dust2 | 13–9 | 0.05 | 25% | 22 Feb → | |
| anubis | 8–13 | 0.14 | 30% | 22 Feb → | |
| ancient | 10–13 | 0.06 | 34% | 20 Feb → | |
| ancient | 13–1 | 0.15 | 38% | 20 Feb → | |
| nuke | 0–10 | 0.03 | 40% | 20 Feb → | |
| mirage | 4–13 | 0.03 | 36% | 17 Feb → | |
| nuke | 7–13 | 0.07 | 26% | 17 Feb → | |
| mirage | 5–13 | 0.12 | 13% | 16 Feb → | |
| dust2 | 0–5 | -0.04 | 10% | 15 Feb → | |
| dust2 | 13–11 | 0.07 | 24% | 15 Feb → | |
| dust2 | 7–13 | 0.03 | 23% | 14 Feb → | |
| inferno | 7–9 | 0.05 | 11% | 13 Feb → | |
| vertigo | 9–7 | 0.02 | 18% | 12 Feb → | |
| ancient | 9–13 | 0.09 | 30% | 11 Feb → | |
| mirage | 2–13 | -0.02 | 12% | 11 Feb → | |
| overpass | 16–12 | 0.10 | 21% | 10 Feb → | |
| nuke | 13–1 | 0.05 | 25% | 10 Feb → | |
| anubis | 13–0 | 0.15 | 31% | 10 Feb → | |
| mirage | 2–13 | 0.04 | 4% | 10 Feb → | |
| nuke | 13–8 | 0.10 | 18% | 9 Feb → | |
| mirage | 5–13 | 0.11 | 32% | 8 Feb → | |
| dust2 | 6–13 | -0.02 | 30% | 5 Feb → | |
| mirage | 10–2 | 0.08 | 24% | 2 Feb → | |
| nuke | 13–9 | 0.11 | 26% | 2 Feb → | |
| mirage | 0–9 | -0.12 | 40% | 1 Feb → | |
| inferno | 5–13 | 0.10 | 20% | 1 Feb → | |
| anubis | 1–13 | -0.00 | 23% | 1 Feb → | |
| dust2 | 0–12 | -0.01 | 35% | 29 Jan → | |
| nuke | 9–1 | 0.25 | 41% | 23 Jan → | |
| overpass | 0–7 | -0.01 | 14% | 23 Jan → | |
| dust2 | 13–4 | 0.04 | 23% | 13 Jan → | |
| train | 12–16 | 0.18 | 27% | 6 Jan → | |
| ancient | 6–13 | 0.10 | 32% | 2 Jan → | |
| vertigo | 7–13 | 0.16 | 25% | 2 Jan → | |
| inferno | 13–8 | 0.04 | 31% | 28 Dec → |
Match data via Leetify.
