I Game With A Half Chub — CS2 Stats
US76561198207131713[U:1:246865985]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Level 10 among CSDB-tracked players (n=3,007), 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 | 46.3% | 52.0% |
| Shot accuracy | 15.1% | 13.7% |
| Kill/death ratio | 1.07 | 1.08 |
| Match win rate | 51.1% | 48.8% |
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -30pp win rate · +0.08 avg rating
Player DNA
Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.
Sharp aimerLimited utility dependence
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 84% playstyle similarity
Most alike: opening-fight frequency, positioning profile.
Where you differ: lower 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 86 — the mechanical foundation is a clear strength.
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. 556ms 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 6.9/10 (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 |
|---|---|---|---|---|---|
| C | 37 | 16–21 | 43% | 0.06 | |
| C | 26 | 11–15 | 42% | 0.07 | |
| A | 11 | 7–4 | 64% | 0.09 | |
| S | 6 | 4–2 | 67% | 0.09 | |
| — | 4 | 2–2 | 50% | 0.08 | |
| thera | — | 4 | 1–3 | 25% | 0.06 |
| — | 4 | 3–1 | 75% | 0.13 | |
| — | 2 | 1–1 | 50% | 0.10 | |
| — | 2 | 0–2 | 0% | 0.05 | |
| — | 2 | 1–1 | 50% | 0.08 | |
| office | — | 1 | 0–1 | 0% | 0.06 |
| agency | — | 1 | 0–1 | 0% | -0.10 |
Across the last 100 tracked matches.
Mirage is currently your weakest sufficiently-sampled map (42% over 26). Start with the 6 essential Mirage 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 resultsWWWLW
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.
- Grenades & UtilityGrenade Lineups →
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.2345 — below the 0.5 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 26 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 2–13 | 0.03 | 25% | 2 Aug → | ||
| 7–13 | -0.02 | 33% | 2 Aug → | ||
| 6–13 | 0.05 | 11% | 7 Jun → | ||
| 13–4 | 0.19 | 13% | 7 Jun → | ||
| 16–13 | 0.11 | 13% | 7 Jun → | ||
| 13–5 | 0.19 | 22% | 10 May → | ||
| 11–13 | 0.24 | 18% | 10 May → | ||
| 12–12 | 0.16 | 11% | 10 May → | ||
| 13–11 | 0.23 | 14% | 10 May → | ||
| 13–9 | 0.13 | 23% | 10 May → | ||
| 13–11 | 0.04 | 21% | 5 May → | ||
| 13–6 | 0.10 | 16% | 4 May → | ||
| 13–6 | -0.05 | 5% | 4 May → | ||
| 13–10 | 0.05 | 13% | 4 May → | ||
| 7–13 | 0.01 | 21% | 2 May → | ||
| 13–10 | 0.08 | 12% | 2 May → | ||
| 13–7 | 0.06 | 56% | 25 Apr → | ||
| 13–4 | 0.07 | 17% | 25 Apr → | ||
| 13–5 | 0.13 | 22% | 7 Apr → | ||
| 4–13 | 0.05 | 28% | 7 Apr → | ||
| 3–13 | 0.03 | 29% | 4 Apr → | ||
| 5–5 | 0.05 | 50% | 4 Apr → | ||
| 7–13 | 0.06 | 38% | 4 Apr → | ||
| 13–11 | 0.11 | 31% | 23 Mar → | ||
| 13–7 | 0.02 | 19% | 15 Dec → | ||
| 13–11 | 0.01 | 17% | 15 Dec → | ||
| 10–13 | 0.13 | 21% | 15 Dec → | ||
| 5–13 | -0.10 | 30% | 13 Dec → | ||
| 4–13 | -0.02 | 33% | 13 Dec → | ||
| 13–11 | -0.03 | 10% | 30 Nov → | ||
| 5–1 | 0.04 | 33% | 23 Nov → | ||
| 8–13 | 0.03 | 47% | 23 Nov → | ||
| 6–13 | -0.03 | 19% | 23 Nov → | ||
| 8–13 | 0.16 | 25% | 11 Nov → | ||
| 0–13 | -0.06 | 22% | 11 Nov → | ||
| 13–2 | 0.11 | 27% | 28 Sept → | ||
| 1–5 | 0.04 | 14% | 26 Aug → | ||
| 7–13 | 0.04 | 14% | 14 Aug → | ||
| 12–12 | 0.02 | 34% | 14 Aug → | ||
| office | 10–13 | 0.06 | 24% | 12 Jul → | |
| 13–7 | 0.05 | 18% | 12 Jul → | ||
| 13–5 | 0.16 | 21% | 21 Jun → | ||
| 11–13 | 0.11 | 23% | 21 Jun → | ||
| 13–5 | 0.06 | 36% | 4 Jun → | ||
| 13–3 | 0.14 | 20% | 4 Jun → | ||
| agency | 2–10 | -0.10 | 40% | 11 May → | |
| 4–13 | -0.10 | 0% | 11 May → | ||
| 5–13 | 0.02 | 14% | 2 May → | ||
| 13–10 | 0.01 | 29% | 20 Apr → | ||
| 0–8 | -0.11 | 33% | 19 Apr → | ||
| 13–3 | 0.16 | 20% | 19 Apr → | ||
| 2–13 | 0.01 | 41% | 13 Apr → | ||
| 2–13 | -0.08 | 35% | 6 Apr → | ||
| 13–2 | 0.22 | 65% | 18 Sept → | ||
| 8–8 | 0.16 | 18% | 15 Sept → | ||
| 7–0 | 0.17 | 26% | 15 Sept → | ||
| 9–3 | 0.17 | 42% | 15 Sept → | ||
| 13–1 | 0.26 | 26% | 14 Sept → | ||
| 13–5 | 0.20 | 24% | 14 Sept → | ||
| 13–9 | 0.10 | 20% | 18 Aug → | ||
| 8–6 | 0.18 | 50% | 22 Jul → | ||
| 13–8 | 0.08 | 28% | 22 Jul → | ||
| 6–13 | -0.04 | 50% | 20 Jul → | ||
| 13–4 | 0.13 | 13% | 20 Jul → | ||
| 12–12 | 0.08 | 21% | 14 Jul → | ||
| 11–13 | 0.08 | 19% | 13 Jul → | ||
| 3–13 | -0.04 | 24% | 9 Jul → | ||
| thera | 5–13 | 0.08 | 25% | 9 Jul → | |
| thera | 0–6 | 0.04 | 50% | 9 Jul → | |
| 13–11 | 0.15 | 26% | 9 Jul → | ||
| 13–7 | 0.12 | 14% | 8 Jul → | ||
| thera | 13–10 | 0.04 | 20% | 8 Jul → | |
| thera | 11–13 | 0.10 | 28% | 7 Jul → | |
| 0–4 | 0.10 | 15% | 15 Apr → | ||
| 13–9 | 0.16 | 21% | 15 Apr → | ||
| 3–8 | 0.09 | 24% | 14 Apr → | ||
| 13–5 | 0.04 | 14% | 12 Apr → | ||
| 9–13 | 0.02 | 24% | 10 Apr → | ||
| 13–8 | 0.14 | 19% | 10 Apr → | ||
| 4–13 | 0.08 | 31% | 9 Apr → | ||
| 9–13 | 0.10 | 16% | 8 Apr → | ||
| 6–13 | 0.02 | 27% | 8 Apr → | ||
| 12–12 | -0.02 | 15% | 7 Apr → | ||
| 8–13 | -0.01 | 34% | 7 Apr → | ||
| 13–9 | 0.07 | 29% | 6 Apr → | ||
| 4–13 | -0.11 | 25% | 5 Apr → | ||
| 2–11 | -0.05 | 25% | 4 Apr → | ||
| 11–13 | 0.15 | 29% | 3 Apr → | ||
| 13–8 | 0.07 | 33% | 3 Apr → | ||
| 8–13 | 0.09 | 23% | 3 Apr → | ||
| 8–13 | -0.01 | 15% | 2 Apr → | ||
| 12–12 | 0.05 | 30% | 2 Apr → | ||
| 3–13 | 0.08 | 26% | 1 Apr → | ||
| 13–8 | 0.09 | 30% | 1 Apr → | ||
| 6–13 | 0.09 | 36% | 1 Apr → | ||
| 1–3 | 0.03 | 100% | 30 Mar → | ||
| 13–10 | 0.12 | 30% | 30 Mar → | ||
| 12–12 | 0.04 | 25% | 30 Mar → | ||
| 13–8 | 0.18 | 29% | 30 Mar → | ||
| 9–5 | 0.19 | 21% | 30 Mar → |
Match data via Leetify.