colblarb — CS2 Stats
76561198442874316[U:1:482608588]
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -10pp win rate · -0.02 avg rating
Player DNA
Primary style: Passive 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 NiKo 78% playstyle similarity
Most alike: utility contribution, opening-duel success.
Where you differ: lower opening-fight frequency; lower aim profile.
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
Reaction time. 568ms 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 4.7/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 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 | 18 | 11–7 | 61% | 0.02 | |
| C | 12 | 5–7 | 42% | 0.04 | |
| D | 11 | 3–8 | 27% | 0.01 | |
| A | 11 | 6–5 | 55% | 0.02 | |
| A | 11 | 6–5 | 55% | 0.05 | |
| B | 10 | 5–5 | 50% | 0.03 | |
| A | 8 | 5–3 | 63% | 0.05 | |
| C | 5 | 2–3 | 40% | 0.00 | |
| S | 5 | 4–1 | 80% | 0.05 | |
| office | — | 4 | 4–0 | 100% | 0.07 |
| — | 3 | 0–3 | 0% | 0.06 | |
| warden | — | 2 | 1–1 | 50% | 0.02 |
Across the last 100 tracked matches.
Mirage is currently your weakest sufficiently-sampled map (27% over 11). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsLLLLW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Inferno | 1 | 0% | 1.12 | 18.0 |
| Ancient | 1 | 100% | 1.25 | 15.0 |
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.
- Best CS2 CrosshairAim Training →
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 11.6788% — below the 15% 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 20.5127% — 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.
27% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 8–13 | 0.03 | 10% | 8 Aug → | ||
| 13–9 | 0.01 | 17% | 26 Jul → | ||
| 12–12 | -0.03 | 10% | 11 Jul → | ||
| 13–11 | 0.02 | 5% | 12 Jun → | ||
| 11–13 | 0.06 | 9% | 7 Jun → | ||
| 9–13 | 0.04 | 7% | 7 Jun → | ||
| 12–1 | 0.02 | 11% | 7 Jun → | ||
| 11–13 | 0.01 | 5% | 3 Jun → | ||
| 13–9 | 0.04 | 9% | 27 May → | ||
| 10–13 | 0.01 | 10% | 27 May → | ||
| 13–10 | 0.03 | 8% | 29 Apr → | ||
| 1–13 | -0.03 | 10% | 25 Apr → | ||
| 13–9 | 0.01 | 23% | 23 Apr → | ||
| office | 13–1 | 0.18 | 5% | 22 Apr → | |
| 13–3 | -0.01 | 19% | 22 Apr → | ||
| 12–12 | 0.03 | 11% | 22 Apr → | ||
| 7–13 | 0.02 | 10% | 21 Apr → | ||
| 1–7 | 0.03 | 7% | 21 Apr → | ||
| 13–8 | 0.13 | 17% | 21 Apr → | ||
| 12–12 | 0.02 | 8% | 21 Apr → | ||
| 8–13 | 0.14 | 15% | 16 Apr → | ||
| 13–2 | 0.16 | 12% | 16 Apr → | ||
| 13–4 | 0.04 | 12% | 12 Apr → | ||
| 12–12 | -0.01 | 10% | 12 Apr → | ||
| 13–3 | 0.09 | 21% | 12 Apr → | ||
| 13–4 | 0.05 | 14% | 12 Apr → | ||
| 7–13 | -0.02 | 5% | 11 Apr → | ||
| 13–6 | 0.07 | 15% | 11 Apr → | ||
| 13–10 | 0.04 | 17% | 10 Apr → | ||
| 13–8 | 0.12 | 21% | 10 Apr → | ||
| 13–2 | 0.18 | 7% | 10 Apr → | ||
| 13–7 | -0.02 | 9% | 10 Apr → | ||
| 7–13 | 0.00 | 7% | 6 Apr → | ||
| 7–13 | 0.08 | 15% | 6 Apr → | ||
| 7–13 | -0.04 | 19% | 6 Apr → | ||
| 10–13 | 0.01 | 13% | 4 Apr → | ||
| 12–12 | 0.08 | 20% | 4 Apr → | ||
| 13–4 | 0.04 | 9% | 4 Apr → | ||
| 13–10 | -0.04 | 11% | 4 Apr → | ||
| 12–12 | -0.07 | 12% | 4 Apr → | ||
| 13–10 | 0.01 | 10% | 4 Apr → | ||
| 13–4 | 0.09 | 8% | 4 Apr → | ||
| 13–4 | 0.12 | 22% | 4 Apr → | ||
| 6–13 | -0.01 | 21% | 4 Apr → | ||
| 1–13 | -0.06 | 20% | 3 Apr → | ||
| 7–13 | -0.04 | 16% | 3 Apr → | ||
| 15–15 | -0.02 | 18% | 3 Apr → | ||
| 13–11 | 0.02 | 8% | 3 Apr → | ||
| 11–13 | 0.08 | 8% | 1 Apr → | ||
| 10–13 | 0.07 | 12% | 1 Apr → | ||
| 13–8 | 0.08 | 4% | 31 Mar → | ||
| 8–13 | -0.06 | 13% | 31 Mar → | ||
| 2–13 | -0.05 | 15% | 31 Mar → | ||
| 12–12 | 0.02 | 14% | 31 Mar → | ||
| 7–13 | 0.01 | 13% | 31 Mar → | ||
| 13–6 | 0.04 | 24% | 30 Mar → | ||
| warden | 12–12 | 0.06 | 0% | 30 Mar → | |
| 13–8 | 0.08 | 19% | 30 Mar → | ||
| warden | 13–11 | -0.01 | 11% | 30 Mar → | |
| 13–4 | 0.07 | 6% | 30 Mar → | ||
| 1–9 | 0.01 | 21% | 30 Mar → | ||
| 13–8 | 0.06 | 9% | 30 Mar → | ||
| 5–13 | -0.03 | 18% | 29 Mar → | ||
| 8–13 | -0.04 | 22% | 29 Mar → | ||
| 13–9 | 0.07 | 16% | 29 Mar → | ||
| 13–11 | 0.04 | 17% | 28 Mar → | ||
| 13–5 | 0.02 | 4% | 27 Mar → | ||
| 12–12 | 0.05 | 10% | 27 Mar → | ||
| 6–13 | -0.01 | 14% | 27 Mar → | ||
| 11–13 | 0.05 | 10% | 25 Mar → | ||
| 15–15 | 0.04 | 13% | 25 Mar → | ||
| 13–9 | 0.02 | 6% | 23 Mar → | ||
| 13–11 | -0.00 | 10% | 23 Mar → | ||
| 13–7 | -0.03 | 6% | 23 Mar → | ||
| 9–13 | -0.00 | 10% | 22 Mar → | ||
| 2–10 | -0.05 | 21% | 22 Mar → | ||
| 9–13 | -0.01 | 6% | 22 Mar → | ||
| 13–11 | 0.06 | 14% | 22 Mar → | ||
| 13–2 | 0.15 | 13% | 22 Mar → | ||
| 13–4 | 0.26 | 11% | 22 Mar → | ||
| 13–3 | -0.02 | 11% | 22 Mar → | ||
| 6–13 | 0.07 | 25% | 22 Mar → | ||
| 13–9 | -0.00 | 11% | 22 Mar → | ||
| 13–4 | 0.07 | 7% | 22 Mar → | ||
| 12–16 | -0.05 | 9% | 19 Mar → | ||
| 10–13 | -0.07 | 11% | 19 Mar → | ||
| 13–11 | 0.07 | 7% | 19 Mar → | ||
| office | 13–4 | 0.07 | 16% | 19 Mar → | |
| office | 13–10 | -0.01 | 6% | 18 Mar → | |
| 13–4 | 0.10 | 10% | 17 Mar → | ||
| 13–8 | 0.09 | 11% | 17 Mar → | ||
| 6–13 | 0.06 | 17% | 17 Mar → | ||
| 13–3 | -0.06 | 8% | 17 Mar → | ||
| 13–3 | 0.04 | 4% | 17 Mar → | ||
| office | 13–6 | 0.03 | 12% | 17 Mar → | |
| 13–4 | 0.09 | 15% | 17 Mar → | ||
| 7–13 | -0.01 | 9% | 17 Mar → | ||
| 1–10 | -0.04 | 22% | 17 Mar → | ||
| 11–13 | -0.05 | 8% | 17 Mar → | ||
| 13–8 | -0.05 | 9% | 17 Mar → |
Match data via Leetify.