Beef — CS2 Stats
76561198072190275[U:1:111924547]Steam profile ↗✓ No bans
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +0pp win rate · -0.03 avg rating
Player DNA
Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.
Sharp aimerStrong CT-side openerLimited 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 93% playstyle similarity
Most alike: opening-fight frequency, opening-duel success.
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 93 — 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
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 67% on CT to 48% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 552ms 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 | 36 | 15–21 | 42% | 0.07 | |
| C | 12 | 5–7 | 42% | 0.10 | |
| B | 12 | 6–6 | 50% | 0.08 | |
| C | 11 | 4–7 | 36% | 0.06 | |
| S | 6 | 4–2 | 67% | 0.12 | |
| D | 6 | 2–4 | 33% | 0.01 | |
| — | 4 | 2–2 | 50% | 0.06 | |
| — | 3 | 2–1 | 67% | 0.21 | |
| — | 3 | 1–2 | 33% | 0.10 | |
| — | 3 | 3–0 | 100% | 0.14 | |
| shelter | — | 2 | 0–2 | 0% | 0.08 |
| office | — | 1 | 0–1 | 0% | 0.10 |
| warden | — | 1 | 1–0 | 100% | 0.05 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (33% over 6). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsLLLWW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 40 | 60% | 1.28 | 18.6 |
| Anubis | 15 | 60% | 1.38 | 23.7 |
| Vertigo | 13 | 77% | 1.75 | 26.1 |
| Dust2 | 13 | 77% | 1.18 | 16.7 |
| Nuke | 9 | 56% | 1.29 | 20.0 |
| Ancient | 9 | 44% | 1.20 | 15.4 |
| Inferno | 8 | 25% | 1.14 | 20.6 |
| Overpass | 4 | 25% | 1.10 | 20.0 |
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
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 0.4893 — 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.
33% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–8 | 0.07 | 47% | 28 Aug → | ||
| 8–13 | 0.02 | 23% | 28 Aug → | ||
| 11–13 | -0.00 | 42% | 22 Aug → | ||
| 13–3 | 0.19 | 43% | 14 Aug → | ||
| 13–2 | 0.08 | 45% | 28 Jul → | ||
| 13–2 | 0.11 | 29% | 28 Jul → | ||
| 13–10 | 0.04 | 33% | 27 Jul → | ||
| 8–13 | 0.09 | 27% | 27 Jul → | ||
| 9–13 | 0.11 | 52% | 27 Jul → | ||
| 12–12 | -0.02 | 31% | 26 Jul → | ||
| 13–11 | 0.16 | 31% | 26 Jul → | ||
| 13–5 | 0.13 | 33% | 26 Jul → | ||
| 13–4 | 0.03 | 35% | 26 Jul → | ||
| 13–3 | 0.22 | 37% | 12 Jul → | ||
| 9–13 | 0.03 | 31% | 12 Jul → | ||
| 4–13 | 0.14 | 17% | 12 Jul → | ||
| shelter | 10–13 | 0.05 | 27% | 12 Jul → | |
| 13–4 | 0.10 | 30% | 9 Jul → | ||
| shelter | 8–13 | 0.10 | 35% | 9 Jul → | |
| 4–13 | 0.07 | 37% | 3 Jul → | ||
| 11–13 | 0.15 | 30% | 3 Jul → | ||
| 4–13 | -0.05 | 28% | 3 Jul → | ||
| 9–7 | 0.05 | 42% | 3 Jul → | ||
| office | 4–13 | 0.10 | 25% | 2 Jul → | |
| 6–13 | 0.05 | 32% | 2 Jul → | ||
| 12–12 | 0.08 | 30% | 2 Jul → | ||
| 11–13 | 0.07 | 29% | 2 Jul → | ||
| 13–0 | 0.25 | 44% | 29 Jun → | ||
| 12–12 | 0.07 | 29% | 29 Jun → | ||
| 6–13 | 0.11 | 16% | 29 Jun → | ||
| 4–13 | 0.05 | 32% | 29 Jun → | ||
| 13–11 | 0.11 | 38% | 27 Jun → | ||
| 7–13 | 0.01 | 34% | 26 Jun → | ||
| 13–5 | 0.19 | 35% | 26 Jun → | ||
| 11–13 | 0.08 | 31% | 16 Jun → | ||
| 13–8 | 0.07 | 34% | 16 Jun → | ||
| 13–10 | 0.10 | 23% | 16 Jun → | ||
| 13–3 | 0.05 | 31% | 16 Jun → | ||
| 5–13 | 0.02 | 26% | 16 May → | ||
| 8–13 | -0.03 | 29% | 16 May → | ||
| 8–13 | 0.05 | 31% | 16 May → | ||
| 6–13 | 0.10 | 35% | 16 May → | ||
| 8–13 | 0.09 | 30% | 11 May → | ||
| 3–13 | 0.02 | 50% | 2 May → | ||
| 13–9 | 0.06 | 31% | 2 May → | ||
| 13–8 | 0.13 | 37% | 2 May → | ||
| 13–7 | 0.09 | 39% | 2 May → | ||
| 11–13 | 0.01 | 33% | 2 May → | ||
| 9–13 | 0.09 | 26% | 2 May → | ||
| 13–4 | 0.05 | 30% | 3 Apr → | ||
| 2–13 | -0.00 | 44% | 13 Mar → | ||
| 5–13 | -0.04 | 18% | 13 Mar → | ||
| 10–13 | 0.02 | 35% | 13 Mar → | ||
| 7–13 | -0.00 | 27% | 10 Mar → | ||
| 13–4 | 0.19 | 20% | 10 Mar → | ||
| 5–13 | 0.03 | 30% | 6 Mar → | ||
| warden | 13–9 | 0.05 | 33% | 18 Feb → | |
| 11–13 | 0.16 | 27% | 17 Feb → | ||
| 13–11 | 0.04 | 26% | 2 Feb → | ||
| 9–4 | 0.19 | 27% | 31 Jan → | ||
| 5–13 | 0.09 | 37% | 28 Jan → | ||
| 15–15 | 0.09 | 32% | 28 Jan → | ||
| 9–13 | 0.01 | 19% | 28 Jan → | ||
| 11–13 | 0.12 | 34% | 28 Jan → | ||
| 13–10 | 0.18 | 24% | 11 Jan → | ||
| 13–10 | 0.05 | 22% | 2 Jan → | ||
| 7–0 | 0.23 | 25% | 29 Dec → | ||
| 9–5 | 0.27 | 27% | 29 Dec → | ||
| 5–9 | -0.03 | 19% | 29 Dec → | ||
| 5–13 | 0.06 | 23% | 29 Dec → | ||
| 13–11 | 0.09 | 23% | 29 Dec → | ||
| 13–4 | 0.13 | 18% | 29 Dec → | ||
| 7–13 | 0.06 | 40% | 15 Dec → | ||
| 11–13 | 0.15 | 27% | 12 Dec → | ||
| 13–3 | 0.03 | 18% | 12 Dec → | ||
| 13–8 | 0.17 | 38% | 12 Dec → | ||
| 13–8 | 0.06 | 24% | 11 Dec → | ||
| 5–13 | 0.04 | 43% | 6 Dec → | ||
| 9–13 | 0.02 | 26% | 6 Dec → | ||
| 9–1 | 0.14 | 33% | 6 Dec → | ||
| 13–5 | 0.07 | 23% | 6 Dec → | ||
| 8–13 | 0.10 | 28% | 6 Dec → | ||
| 10–13 | 0.07 | 31% | 2 Dec → | ||
| 13–1 | 0.07 | 24% | 2 Dec → | ||
| 4–13 | 0.03 | 27% | 2 Dec → | ||
| 7–13 | -0.00 | 25% | 2 Dec → | ||
| 13–3 | 0.22 | 32% | 2 Dec → | ||
| 13–4 | 0.09 | 33% | 29 Nov → | ||
| 13–10 | 0.04 | 31% | 23 Nov → | ||
| 13–10 | 0.11 | 58% | 20 Nov → | ||
| 12–12 | 0.12 | 31% | 20 Nov → | ||
| 13–8 | 0.11 | 38% | 19 Nov → | ||
| 11–13 | 0.08 | 35% | 18 Nov → | ||
| 2–13 | -0.01 | 38% | 18 Nov → | ||
| 13–8 | 0.15 | 34% | 18 Nov → | ||
| 13–4 | 0.24 | 35% | 17 Nov → | ||
| 8–13 | 0.08 | 25% | 17 Nov → | ||
| 10–13 | 0.09 | 28% | 16 Nov → | ||
| 13–9 | 0.10 | 20% | 16 Nov → | ||
| 1–13 | -0.07 | 23% | 11 Nov → |
Match data via Leetify.