✪ Scoobert — CS2 Stats
76561198004579329[U:1:44313601]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Level 1 among CSDB-tracked players (n=230), 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 1 median | Level 2 median | vs Level 2 |
|---|---|---|---|---|
| Headshot rate | 40.7% | 41.1% | 41.2% | meets |
| Shot accuracy | 18.8% | 14.1% | 12.5% | above |
| Kill/death ratio | 1.35 | 0.97 | 0.96 | above |
| Match win rate | 47.4% | 41.9% | 42.8% | above |
Across every metric we can compare, this profile already matches the typical Level 2 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 · -0.02 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
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 ropz 91% playstyle similarity
Most alike: opening-fight frequency, utility contribution.
Where you differ: lower aim profile; lower opening-duel success.
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 31 points — deaths here waste a strong aim profile.
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
Reaction time. 628ms 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 (×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 |
|---|---|---|---|---|---|
| A | 28 | 16–12 | 57% | 0.02 | |
| B | 21 | 10–11 | 48% | 0.01 | |
| office | C | 12 | 5–7 | 42% | -0.00 |
| C | 11 | 4–7 | 36% | -0.00 | |
| S | 10 | 9–1 | 90% | 0.02 | |
| A | 9 | 5–4 | 56% | -0.00 | |
| — | 4 | 2–2 | 50% | -0.01 | |
| — | 2 | 1–1 | 50% | 0.02 | |
| warden | — | 1 | 1–0 | 100% | 0.12 |
| — | 1 | 1–0 | 100% | 0.01 | |
| — | 1 | 0–1 | 0% | 0.06 |
Across the last 100 tracked matches.
Nuke is currently your weakest sufficiently-sampled map (36% over 11). 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
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 0.4698 — below the 0.5 mark we flag
- 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 34.7276% — 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.
36% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–11 | 0.00 | 26% | 31 Aug → | ||
| 13–6 | 0.06 | 18% | 30 Aug → | ||
| 13–8 | -0.06 | 12% | 30 Aug → | ||
| 16–14 | -0.02 | 18% | 30 Aug → | ||
| 5–13 | -0.04 | 42% | 30 Aug → | ||
| 12–12 | -0.03 | 24% | 28 Aug → | ||
| 13–11 | -0.01 | 8% | 28 Aug → | ||
| office | 9–13 | 0.01 | 42% | 20 Aug → | |
| 11–13 | -0.00 | 20% | 15 Aug → | ||
| 13–9 | 0.02 | 13% | 15 Aug → | ||
| 13–4 | 0.06 | 22% | 15 Aug → | ||
| office | 13–9 | 0.05 | 9% | 8 Feb → | |
| 13–3 | 0.09 | 27% | 7 Feb → | ||
| office | 12–12 | 0.01 | 14% | 7 Feb → | |
| 13–11 | 0.00 | 16% | 7 Feb → | ||
| 13–7 | -0.01 | 16% | 7 Feb → | ||
| office | 13–8 | -0.00 | 17% | 7 Feb → | |
| 9–13 | 0.05 | 12% | 7 Feb → | ||
| 8–13 | -0.03 | 26% | 7 Feb → | ||
| 3–13 | -0.05 | 32% | 6 Feb → | ||
| 13–9 | -0.02 | 26% | 6 Feb → | ||
| office | 13–3 | 0.06 | 9% | 2 Feb → | |
| 12–12 | 0.04 | 22% | 2 Feb → | ||
| 5–13 | -0.09 | 15% | 2 Feb → | ||
| 13–5 | -0.02 | 10% | 2 Feb → | ||
| office | 11–13 | -0.05 | 12% | 2 Feb → | |
| 13–7 | -0.03 | 20% | 28 Jan → | ||
| 5–13 | -0.06 | 8% | 28 Jan → | ||
| office | 13–9 | 0.04 | 32% | 27 Jan → | |
| 13–7 | 0.10 | 47% | 26 Jan → | ||
| 4–13 | 0.02 | 25% | 26 Jan → | ||
| 16–12 | 0.02 | 17% | 26 Jan → | ||
| 7–13 | 0.00 | 50% | 26 Jan → | ||
| warden | 13–6 | 0.12 | 18% | 26 Jan → | |
| 9–13 | -0.06 | 5% | 26 Jan → | ||
| 13–11 | 0.01 | 13% | 26 Jan → | ||
| 15–15 | 0.05 | 20% | 25 Jan → | ||
| office | 1–13 | -0.04 | 27% | 25 Jan → | |
| 6–13 | -0.06 | 11% | 18 Jan → | ||
| 13–10 | 0.04 | 40% | 18 Jan → | ||
| office | 3–10 | -0.01 | 56% | 17 Jan → | |
| 13–8 | 0.06 | 29% | 17 Jan → | ||
| office | 13–10 | 0.02 | 17% | 16 Jan → | |
| 13–2 | 0.06 | 32% | 16 Jan → | ||
| 13–6 | -0.04 | 6% | 16 Jan → | ||
| 8–13 | -0.05 | 27% | 16 Jan → | ||
| 12–12 | 0.02 | 20% | 11 Jan → | ||
| 10–10 | -0.02 | 17% | 11 Jan → | ||
| 9–13 | 0.08 | 34% | 11 Jan → | ||
| 13–10 | 0.04 | 19% | 11 Jan → | ||
| 6–13 | -0.03 | 24% | 11 Jan → | ||
| office | 3–13 | -0.04 | 45% | 11 Jan → | |
| 13–11 | 0.01 | 15% | 11 Jan → | ||
| 13–11 | 0.08 | 30% | 10 Jan → | ||
| 8–13 | -0.06 | 8% | 8 Jan → | ||
| 13–16 | -0.04 | 17% | 8 Jan → | ||
| office | 12–12 | -0.05 | 30% | 4 Jan → | |
| 13–11 | 0.07 | 15% | 4 Jan → | ||
| 8–13 | 0.01 | 30% | 4 Jan → | ||
| 13–6 | -0.03 | 21% | 4 Jan → | ||
| 16–12 | -0.00 | 13% | 4 Jan → | ||
| 13–9 | 0.04 | 16% | 3 Jan → | ||
| 10–13 | 0.03 | 25% | 3 Jan → | ||
| 13–10 | 0.02 | 19% | 3 Jan → | ||
| 13–11 | 0.01 | 28% | 3 Jan → | ||
| 13–11 | -0.04 | 19% | 3 Jan → | ||
| 13–4 | 0.02 | 35% | 3 Jan → | ||
| 13–11 | 0.00 | 25% | 1 Jan → | ||
| 3–13 | -0.03 | 28% | 1 Jan → | ||
| 9–13 | 0.01 | 23% | 1 Jan → | ||
| 13–5 | 0.02 | 20% | 1 Jan → | ||
| 9–13 | -0.01 | 21% | 1 Jan → | ||
| 13–8 | -0.01 | 26% | 31 Dec → | ||
| 11–6 | 0.02 | 55% | 31 Dec → | ||
| 13–11 | -0.05 | 31% | 31 Dec → | ||
| 13–7 | 0.04 | 59% | 31 Dec → | ||
| 11–13 | 0.06 | 24% | 30 Dec → | ||
| 11–13 | 0.08 | 24% | 30 Dec → | ||
| 13–5 | 0.05 | 29% | 26 Dec → | ||
| 16–12 | 0.00 | 28% | 26 Dec → | ||
| 9–13 | -0.02 | 18% | 25 Dec → | ||
| 13–8 | 0.15 | 31% | 25 Dec → | ||
| 9–13 | 0.00 | 28% | 25 Dec → | ||
| 7–13 | -0.00 | 34% | 25 Dec → | ||
| 13–8 | -0.01 | 27% | 25 Dec → | ||
| 15–15 | -0.01 | 26% | 25 Dec → | ||
| 13–1 | 0.06 | 25% | 25 Dec → | ||
| 13–6 | 0.04 | 12% | 24 Dec → | ||
| 13–5 | 0.14 | 24% | 24 Dec → | ||
| 13–1 | 0.09 | 35% | 24 Dec → | ||
| 14–16 | 0.01 | 56% | 23 Dec → | ||
| 10–13 | 0.11 | 22% | 23 Dec → | ||
| 9–13 | 0.06 | 32% | 22 Dec → | ||
| 8–13 | 0.06 | 47% | 22 Dec → | ||
| 13–6 | -0.01 | 30% | 22 Dec → | ||
| 9–13 | -0.06 | 22% | 21 Dec → | ||
| 13–11 | 0.02 | 21% | 21 Dec → | ||
| 9–13 | 0.01 | 18% | 21 Dec → | ||
| 11–13 | 0.01 | 20% | 21 Dec → | ||
| 9–13 | -0.03 | 7% | 21 Dec → |
Match data via Leetify.