hhS — CS2 Stats
AU76561198116279938[U:1:156014210]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Level 3 among CSDB-tracked players (n=1,149), 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 3 median | Level 4 median | vs Level 4 |
|---|---|---|---|---|
| Headshot rate | 55.5% | 42.2% | 42.7% | above |
| Shot accuracy | 26.1% | 11.9% | 10.8% | above |
| Kill/death ratio | 2.21 | 0.98 | 1.00 | above |
| Match win rate | 47.5% | 43.6% | 44.1% | above |
Across every metric we can compare, this profile already matches the typical Level 4 player. Rank still comes from winning matches — this is a performance comparison, not a prediction.
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +40pp 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-strafing
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 donk 95% playstyle similarity
Most alike: opening-duel success, opening-fight frequency.
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 91 — the mechanical foundation is a clear strength.
Counter-strafing. 91% of shots taken properly stopped — movement discipline most players never reach.
Areas to improve
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
Reaction time. 563ms 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 6.7/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 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 |
|---|---|---|---|---|---|
| B | 21 | 10–11 | 48% | 0.01 | |
| B | 17 | 8–9 | 47% | 0.02 | |
| B | 15 | 8–7 | 53% | 0.03 | |
| A | 14 | 8–6 | 57% | 0.01 | |
| A | 9 | 5–4 | 56% | 0.02 | |
| S | 9 | 6–3 | 67% | 0.05 | |
| D | 8 | 2–6 | 25% | -0.01 | |
| B | 6 | 3–3 | 50% | 0.01 | |
| boulder | — | 1 | 0–1 | 0% | 0.05 |
Across the last 100 tracked matches.
Nuke is currently your weakest sufficiently-sampled map (25% over 8). 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.
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.
25% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 2–13 | -0.04 | 7% | 29 Aug → | ||
| 13–11 | 0.04 | 18% | 29 Aug → | ||
| 16–14 | 0.06 | 18% | 29 Aug → | ||
| 1–1 | 0.09 | 50% | 29 Aug → | ||
| 13–11 | 0.02 | 10% | 28 Aug → | ||
| 16–12 | 0.08 | 9% | 28 Aug → | ||
| 13–7 | 0.05 | 21% | 28 Aug → | ||
| 13–8 | 0.04 | 24% | 28 Aug → | ||
| 15–15 | 0.01 | 16% | 25 Aug → | ||
| 13–9 | -0.02 | 24% | 25 Aug → | ||
| 10–13 | 0.01 | 20% | 25 Aug → | ||
| 11–13 | -0.01 | 17% | 23 Aug → | ||
| 13–7 | -0.01 | 23% | 23 Aug → | ||
| boulder | 6–13 | 0.05 | 15% | 23 Aug → | |
| 7–13 | -0.00 | 15% | 23 Aug → | ||
| 5–13 | -0.01 | 10% | 22 Aug → | ||
| 13–10 | 0.08 | 8% | 22 Aug → | ||
| 13–9 | 0.05 | 9% | 22 Aug → | ||
| 6–13 | -0.03 | 7% | 22 Aug → | ||
| 11–13 | 0.04 | 22% | 22 Aug → | ||
| 13–16 | -0.01 | 16% | 21 Aug → | ||
| 15–15 | 0.03 | 25% | 21 Aug → | ||
| 6–13 | 0.01 | 23% | 21 Aug → | ||
| 7–13 | 0.01 | 24% | 25 Jun → | ||
| 7–13 | 0.01 | 23% | 23 Jun → | ||
| 8–13 | -0.04 | 20% | 21 Jun → | ||
| 13–9 | 0.04 | 17% | 20 Jun → | ||
| 10–13 | -0.01 | 17% | 20 Jun → | ||
| 13–7 | 0.07 | 24% | 20 Jun → | ||
| 15–15 | 0.03 | 22% | 20 Jun → | ||
| 8–13 | -0.01 | 15% | 17 May → | ||
| 13–10 | 0.00 | 24% | 17 May → | ||
| 9–13 | -0.03 | 22% | 26 Apr → | ||
| 16–12 | 0.04 | 16% | 26 Apr → | ||
| 13–4 | 0.14 | 16% | 7 Apr → | ||
| 13–11 | 0.04 | 23% | 7 Apr → | ||
| 13–7 | 0.15 | 13% | 7 Apr → | ||
| 6–13 | 0.03 | 22% | 7 Apr → | ||
| 10–13 | -0.06 | 25% | 1 Apr → | ||
| 12–16 | -0.04 | 22% | 1 Apr → | ||
| 13–4 | 0.09 | 18% | 30 Mar → | ||
| 13–11 | -0.02 | 15% | 30 Mar → | ||
| 13–5 | 0.03 | 25% | 30 Mar → | ||
| 13–10 | -0.01 | 11% | 28 Mar → | ||
| 8–13 | -0.01 | 22% | 28 Mar → | ||
| 10–13 | -0.01 | 13% | 28 Mar → | ||
| 0–13 | -0.08 | 22% | 28 Mar → | ||
| 9–13 | 0.01 | 20% | 28 Mar → | ||
| 6–13 | 0.01 | 12% | 21 Mar → | ||
| 13–6 | 0.03 | 21% | 21 Mar → | ||
| 13–4 | 0.07 | 10% | 21 Mar → | ||
| 10–13 | -0.01 | 17% | 20 Mar → | ||
| 13–5 | 0.03 | 11% | 20 Mar → | ||
| 13–9 | -0.01 | 11% | 20 Mar → | ||
| 13–9 | 0.05 | 20% | 20 Mar → | ||
| 10–13 | 0.00 | 20% | 20 Mar → | ||
| 13–11 | 0.01 | 19% | 20 Mar → | ||
| 13–5 | 0.04 | 21% | 18 Mar → | ||
| 13–10 | 0.04 | 11% | 18 Mar → | ||
| 7–2 | -0.02 | 47% | 18 Mar → | ||
| 13–6 | 0.07 | 19% | 18 Mar → | ||
| 13–5 | 0.03 | 25% | 16 Mar → | ||
| 13–4 | 0.08 | 11% | 16 Mar → | ||
| 8–13 | -0.04 | 19% | 16 Mar → | ||
| 9–13 | 0.00 | 8% | 3 Mar → | ||
| 10–13 | 0.02 | 27% | 3 Mar → | ||
| 9–13 | -0.03 | 20% | 3 Mar → | ||
| 8–13 | -0.01 | 13% | 28 Feb → | ||
| 6–1 | -0.04 | 11% | 28 Feb → | ||
| 13–11 | -0.01 | 10% | 28 Feb → | ||
| 6–13 | -0.08 | 13% | 28 Feb → | ||
| 13–8 | 0.07 | 36% | 28 Feb → | ||
| 9–13 | 0.02 | 19% | 28 Feb → | ||
| 9–13 | 0.03 | 20% | 27 Feb → | ||
| 15–15 | 0.08 | 20% | 27 Feb → | ||
| 13–11 | -0.01 | 13% | 23 Feb → | ||
| 8–13 | -0.04 | 13% | 23 Feb → | ||
| 4–13 | 0.03 | 24% | 23 Feb → | ||
| 13–8 | 0.04 | 17% | 22 Feb → | ||
| 11–13 | 0.06 | 21% | 22 Feb → | ||
| 13–10 | -0.03 | 13% | 21 Feb → | ||
| 5–13 | -0.03 | 10% | 21 Feb → | ||
| 4–13 | -0.03 | 13% | 21 Feb → | ||
| 7–13 | -0.02 | 18% | 21 Feb → | ||
| 13–4 | 0.06 | 21% | 21 Feb → | ||
| 16–14 | -0.06 | 19% | 21 Feb → | ||
| 13–6 | 0.04 | 26% | 19 Feb → | ||
| 13–5 | 0.08 | 15% | 18 Feb → | ||
| 13–11 | -0.03 | 8% | 18 Feb → | ||
| 11–13 | -0.01 | 20% | 18 Feb → | ||
| 1–13 | -0.04 | 22% | 18 Feb → | ||
| 13–8 | 0.04 | 18% | 18 Feb → | ||
| 13–5 | 0.14 | 22% | 18 Feb → | ||
| 13–7 | 0.05 | 16% | 16 Feb → | ||
| 10–13 | 0.01 | 16% | 16 Feb → | ||
| 13–5 | 0.05 | 11% | 16 Feb → | ||
| 13–3 | 0.11 | 15% | 16 Feb → | ||
| 9–13 | 0.08 | 22% | 15 Feb → | ||
| 13–10 | 0.06 | 5% | 15 Feb → | ||
| 11–13 | 0.03 | 21% | 15 Feb → |
Match data via Leetify.
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