bet0n — CS2 Stats
76561198382358973[U:1:422093245]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Pink band among CSDB-tracked players (n=201), 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 | Pink band median | vs Pink band |
|---|---|---|---|
| Headshot rate | 51.5% | 48.1% | above |
| Shot accuracy | 14.3% | 12.9% | above |
| Kill/death ratio | 1.20 | 1.08 | above |
| Match win rate | 47.6% | 46.5% | above |
Across every metric we can compare, this profile already matches the typical Pink band 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: +0pp win rate · +0.04 avg rating
Player DNA
Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.
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 Twistzz 92% playstyle similarity
Most alike: opening-duel success, opening-fight frequency.
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
Areas to improve
Positioning. Positioning trails aim by 32 points — deaths here waste a strong aim profile.
Reaction time. 574ms 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 5.8/10 (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 | 54 | 21–33 | 39% | 0.01 | |
| B | 13 | 6–7 | 46% | 0.07 | |
| A | 11 | 7–4 | 64% | 0.02 | |
| D | 9 | 3–6 | 33% | 0.01 | |
| — | 4 | 2–2 | 50% | -0.00 | |
| — | 3 | 2–1 | 67% | 0.07 | |
| — | 2 | 0–2 | 0% | -0.04 | |
| — | 2 | 0–2 | 0% | 0.03 | |
| — | 1 | 1–0 | 100% | 0.10 | |
| — | 1 | 1–0 | 100% | 0.04 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Anubis 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 resultsLLWWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Dust2 | 199 | 61% | 1.36 | 19.7 |
| Mirage | 166 | 49% | 1.20 | 18.9 |
| Anubis | 155 | 52% | 1.27 | 19.3 |
| Inferno | 69 | 49% | 1.25 | 19.8 |
| Nuke | 31 | 45% | 1.24 | 19.7 |
| Ancient | 28 | 54% | 1.12 | 18.4 |
| Vertigo | 16 | 81% | 1.77 | 19.2 |
| Train | 15 | 53% | 1.36 | 18.6 |
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.
- Advanced Mechanics
You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.
T opening duels 32.4453% — below the 40% 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 9 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–9 | 0.00 | 16% | 26 Aug → | ||
| 4–13 | 0.01 | 32% | 25 Aug → | ||
| 12–12 | 0.07 | 17% | 25 Aug → | ||
| 6–13 | 0.03 | 20% | 2 Aug → | ||
| 10–13 | -0.01 | 25% | 2 Aug → | ||
| 7–13 | 0.01 | 27% | 1 Aug → | ||
| 13–6 | 0.07 | 10% | 29 Jul → | ||
| 11–13 | 0.06 | 23% | 28 Jul → | ||
| 5–13 | -0.08 | 31% | 27 Jul → | ||
| 13–9 | -0.02 | 16% | 27 Jul → | ||
| 9–13 | 0.03 | 26% | 26 Jul → | ||
| 13–4 | 0.07 | 18% | 26 Jul → | ||
| 13–10 | -0.04 | 23% | 24 Jul → | ||
| 13–7 | 0.02 | 20% | 22 Jul → | ||
| 2–13 | -0.04 | 26% | 22 Jul → | ||
| 6–13 | -0.06 | 10% | 21 Jul → | ||
| 6–13 | -0.08 | 28% | 19 Jul → | ||
| 9–13 | -0.01 | 37% | 19 Jul → | ||
| 7–13 | -0.07 | 31% | 19 Jul → | ||
| 8–13 | -0.06 | 20% | 18 Jul → | ||
| 13–11 | -0.01 | 26% | 18 Jul → | ||
| 13–9 | 0.10 | 25% | 15 Jul → | ||
| 3–13 | -0.03 | 16% | 15 Jul → | ||
| 13–10 | 0.05 | 21% | 15 Jul → | ||
| 13–4 | 0.07 | 14% | 15 Jul → | ||
| 10–13 | -0.00 | 20% | 15 Jul → | ||
| 13–9 | 0.05 | 33% | 14 Jul → | ||
| 1–13 | -0.07 | 25% | 9 Jul → | ||
| 10–13 | -0.04 | 12% | 9 Jul → | ||
| 11–13 | 0.06 | 22% | 9 Jul → | ||
| 11–13 | -0.06 | 35% | 2 Jul → | ||
| 8–13 | 0.01 | 20% | 27 Jun → | ||
| 9–13 | -0.00 | 20% | 26 Jun → | ||
| 13–7 | 0.06 | 18% | 22 Jun → | ||
| 11–13 | 0.00 | 18% | 22 Jun → | ||
| 13–6 | 0.04 | 25% | 21 Jun → | ||
| 10–13 | 0.04 | 24% | 14 Jun → | ||
| 11–13 | -0.03 | 24% | 14 Jun → | ||
| 6–13 | -0.01 | 22% | 9 Jun → | ||
| 11–13 | 0.02 | 20% | 4 Jun → | ||
| 13–6 | -0.04 | 14% | 3 Jun → | ||
| 11–13 | -0.02 | 25% | 2 Jun → | ||
| 13–7 | 0.05 | 32% | 29 May → | ||
| 13–2 | 0.10 | 24% | 29 May → | ||
| 6–13 | -0.03 | 29% | 28 May → | ||
| 6–13 | -0.03 | 36% | 28 May → | ||
| 12–12 | 0.07 | 25% | 20 May → | ||
| 13–10 | 0.01 | 22% | 20 May → | ||
| 7–13 | -0.05 | 17% | 17 May → | ||
| 9–13 | 0.22 | 31% | 16 May → | ||
| 10–13 | -0.01 | 38% | 6 May → | ||
| 13–4 | 0.09 | 21% | 3 May → | ||
| 7–13 | 0.04 | 26% | 30 Apr → | ||
| 2–3 | 0.23 | 18% | 29 Apr → | ||
| 13–10 | 0.04 | 16% | 29 Apr → | ||
| 13–4 | 0.02 | 28% | 24 Apr → | ||
| 6–13 | -0.05 | 19% | 22 Apr → | ||
| 10–13 | 0.01 | 17% | 22 Apr → | ||
| 13–5 | 0.07 | 33% | 22 Apr → | ||
| 13–9 | 0.15 | 21% | 15 Apr → | ||
| 12–12 | 0.15 | 20% | 11 Apr → | ||
| 10–13 | -0.05 | 29% | 10 Apr → | ||
| 13–0 | 0.05 | 11% | 8 Apr → | ||
| 13–9 | 0.02 | 14% | 7 Apr → | ||
| 9–2 | 0.29 | 30% | 3 Apr → | ||
| 13–8 | 0.06 | 18% | 27 Mar → | ||
| 10–13 | -0.03 | 10% | 22 Mar → | ||
| 14–16 | 0.02 | 14% | 18 Mar → | ||
| 3–13 | 0.00 | 16% | 18 Mar → | ||
| 2–13 | 0.06 | 22% | 18 Mar → | ||
| 15–15 | 0.05 | 29% | 18 Mar → | ||
| 13–16 | 0.02 | 22% | 11 Mar → | ||
| 4–10 | -0.09 | 17% | 6 Mar → | ||
| 11–13 | 0.00 | 27% | 5 Mar → | ||
| 13–8 | 0.02 | 24% | 5 Mar → | ||
| 13–10 | 0.03 | 18% | 5 Mar → | ||
| 13–9 | -0.07 | 20% | 3 Mar → | ||
| 7–13 | 0.00 | 26% | 25 Feb → | ||
| 13–11 | 0.01 | 15% | 11 Feb → | ||
| 13–11 | 0.07 | 23% | 11 Feb → | ||
| 3–13 | -0.04 | 27% | 7 Feb → | ||
| 13–8 | 0.13 | 29% | 7 Feb → | ||
| 5–13 | -0.05 | 35% | 6 Feb → | ||
| 7–13 | -0.01 | 48% | 2 Feb → | ||
| 13–11 | 0.01 | 21% | 28 Jan → | ||
| 9–6 | -0.06 | 19% | 28 Jan → | ||
| 13–2 | 0.09 | 28% | 23 Jan → | ||
| 13–10 | 0.13 | 16% | 21 Jan → | ||
| 11–13 | 0.03 | 22% | 21 Jan → | ||
| 13–10 | 0.06 | 16% | 14 Jan → | ||
| 13–10 | 0.04 | 20% | 7 Jan → | ||
| 11–13 | 0.03 | 21% | 2 Jan → | ||
| 13–9 | 0.01 | 27% | 31 Dec → | ||
| 5–13 | 0.05 | 30% | 31 Dec → | ||
| 13–10 | 0.02 | 22% | 27 Dec → | ||
| 7–13 | 0.01 | 30% | 27 Dec → | ||
| 13–8 | 0.01 | 27% | 26 Dec → | ||
| 13–1 | 0.13 | 25% | 25 Dec → | ||
| 13–9 | 0.04 | 22% | 25 Dec → | ||
| 10–13 | -0.04 | 28% | 24 Dec → |
Match data via Leetify.