roberto — CS2 Stats
CA76561198023683249[U:1:63417521]Steam profile ↗✓ No bans
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -30pp win rate · -0.00 avg rating
Player DNA
Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.
Sharp aimerExcellent counter-strafing
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 95% playstyle similarity
Most alike: opening-duel success, 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 88 — the mechanical foundation is a clear strength.
Areas to improve
Positioning. Positioning trails aim by 35 points — deaths here waste a strong aim profile.
Reaction time. 570ms 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 6.8/10 (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 |
|---|---|---|---|---|---|
 inferno | A | 21 | 13–8 | 62% | 0.03 |
 mirage | S | 20 | 13–7 | 65% | 0.05 |
 anubis | S | 12 | 8–4 | 67% | 0.02 |
 dust2 | B | 11 | 5–6 | 45% | 0.04 |
 cache | A | 11 | 7–4 | 64% | 0.05 |
 ancient | C | 10 | 4–6 | 40% | 0.01 |
 nuke | C | 7 | 3–4 | 43% | -0.00 |
 overpass | S | 6 | 4–2 | 67% | 0.01 |
| debris | — | 1 | 1–0 | 100% | 0.10 |
 vertigo | — | 1 | 0–1 | 0% | -0.05 |
Across the last 100 tracked matches.
Ancient is currently your weakest sufficiently-sampled map (40% over 10). Start with the 6 essential Ancient 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 resultsLLWLW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 42 | 55% | 1.19 | 15.9 |
| Anubis | 41 | 49% | 1.10 | 16.4 |
| Dust2 | 40 | 48% | 1.13 | 15.3 |
| Ancient | 27 | 52% | 1.03 | 17.3 |
| Inferno | 24 | 58% | 1.25 | 17.2 |
| Nuke | 4 | 25% | 0.92 | 15.8 |
| Train | 2 | 0% | 1.12 | 19.0 |
| Vertigo | 2 | 50% | 0.94 | 13.5 |
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
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 36.2013% — 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.
40% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| ancient | 16–12 | 0.08 | 21% | 16 Aug → | |
| dust2 | 13–16 | 0.05 | 32% | 11 Aug → | |
| mirage | 13–10 | 0.06 | 17% | 11 Aug → | |
| nuke | 6–13 | 0.02 | 35% | 11 Aug → | |
| ancient | 13–5 | 0.04 | 24% | 1 Aug → | |
| inferno | 6–13 | -0.04 | 15% | 1 Aug → | |
| inferno | 12–16 | 0.01 | 22% | 31 Jul → | |
| cache | 15–15 | 0.00 | 31% | 31 Jul → | |
| anubis | 7–13 | 0.02 | 24% | 31 Jul → | |
| cache | 7–1 | 0.12 | 18% | 29 Jul → | |
| dust2 | 15–15 | 0.02 | 31% | 29 Jul → | |
| anubis | 13–11 | 0.01 | 14% | 27 Jul → | |
| inferno | 13–9 | 0.01 | 26% | 27 Jul → | |
| nuke | 13–11 | 0.03 | 33% | 22 Jul → | |
| mirage | 5–13 | -0.01 | 17% | 10 Jul → | |
| cache | 13–8 | 0.08 | 41% | 9 Jul → | |
| inferno | 9–7 | 0.17 | 32% | 8 Jul → | |
| debris | 9–6 | 0.10 | 16% | 8 Jul → | |
| inferno | 2–9 | -0.03 | 41% | 6 Jul → | |
| anubis | 13–5 | 0.01 | 31% | 4 Jul → | |
| inferno | 11–13 | -0.02 | 19% | 4 Jul → | |
| overpass | 13–8 | 0.03 | 23% | 4 Jul → | |
| inferno | 16–14 | -0.00 | 19% | 4 Jul → | |
| anubis | 14–16 | -0.03 | 12% | 2 Jul → | |
| mirage | 5–13 | 0.02 | 26% | 1 Jul → | |
| inferno | 13–11 | -0.04 | 44% | 30 Jun → | |
| mirage | 13–8 | 0.09 | 35% | 30 Jun → | |
| inferno | 13–11 | 0.05 | 17% | 19 Jun → | |
| nuke | 5–13 | -0.06 | 20% | 19 Jun → | |
| mirage | 8–13 | 0.01 | 17% | 19 Jun → | |
| anubis | 7–13 | -0.01 | 18% | 19 Jun → | |
| mirage | 13–11 | 0.07 | 21% | 18 Jun → | |
| mirage | 13–10 | -0.01 | 23% | 18 Jun → | |
| inferno | 13–8 | 0.05 | 33% | 18 Jun → | |
| overpass | 13–8 | 0.05 | 28% | 16 Jun → | |
| nuke | 0–13 | -0.08 | 0% | 15 Jun → | |
| ancient | 12–16 | -0.06 | 23% | 15 Jun → | |
| nuke | 13–8 | 0.04 | 24% | 11 Jun → | |
| mirage | 11–13 | 0.01 | 40% | 11 Jun → | |
| ancient | 11–13 | -0.03 | 30% | 11 Jun → | |
| anubis | 6–13 | -0.03 | 28% | 11 Jun → | |
| dust2 | 13–7 | 0.06 | 22% | 11 Jun → | |
| cache | 8–13 | 0.11 | 23% | 9 Jun → | |
| anubis | 13–5 | 0.01 | 12% | 9 Jun → | |
| ancient | 8–13 | -0.04 | 26% | 9 Jun → | |
| overpass | 13–9 | 0.01 | 19% | 8 Jun → | |
| mirage | 8–13 | 0.02 | 22% | 8 Jun → | |
| inferno | 13–3 | 0.02 | 15% | 8 Jun → | |
| inferno | 13–7 | 0.07 | 31% | 7 Jun → | |
| mirage | 13–0 | 0.09 | 26% | 7 Jun → | |
| ancient | 13–16 | 0.01 | 23% | 7 Jun → | |
| ancient | 11–13 | 0.06 | 16% | 7 Jun → | |
| nuke | 13–10 | 0.03 | 28% | 5 Jun → | |
| ancient | 15–15 | 0.04 | 18% | 5 Jun → | |
| anubis | 13–6 | 0.10 | 24% | 5 Jun → | |
| mirage | 13–9 | 0.07 | 36% | 4 Jun → | |
| anubis | 13–11 | 0.02 | 13% | 4 Jun → | |
| overpass | 8–13 | -0.04 | 20% | 3 Jun → | |
| inferno | 13–9 | 0.07 | 16% | 3 Jun → | |
| dust2 | 14–16 | 0.02 | 29% | 3 Jun → | |
| ancient | 13–4 | 0.06 | 29% | 3 Jun → | |
| mirage | 6–13 | 0.04 | 34% | 1 Jun → | |
| ancient | 13–10 | -0.01 | 19% | 1 Jun → | |
| inferno | 8–8 | -0.04 | 29% | 29 May → | |
| inferno | 8–8 | -0.09 | 16% | 29 May → | |
| mirage | 13–1 | 0.16 | 35% | 28 May → | |
| mirage | 13–7 | 0.04 | 23% | 28 May → | |
| inferno | 14–16 | 0.07 | 25% | 27 May → | |
| nuke | 15–15 | 0.01 | 26% | 21 May → | |
| anubis | 13–9 | 0.00 | 13% | 21 May → | |
| dust2 | 9–13 | 0.02 | 13% | 19 May → | |
| mirage | 13–8 | 0.06 | 20% | 19 May → | |
| anubis | 13–4 | 0.03 | 22% | 19 May → | |
| mirage | 13–5 | -0.00 | 34% | 19 May → | |
| inferno | 8–13 | 0.09 | 49% | 18 May → | |
| inferno | 16–13 | 0.07 | 30% | 17 May → | |
| inferno | 13–11 | 0.04 | 21% | 17 May → | |
| overpass | 4–13 | -0.04 | 21% | 17 May → | |
| overpass | 16–13 | 0.01 | 22% | 16 May → | |
| mirage | 16–14 | 0.09 | 20% | 16 May → | |
| dust2 | 13–2 | 0.07 | 42% | 16 May → | |
| dust2 | 5–12 | 0.07 | 29% | 14 May → | |
| dust2 | 13–8 | 0.04 | 32% | 14 May → | |
| inferno | 13–4 | 0.03 | 28% | 14 May → | |
| mirage | 13–2 | 0.12 | 36% | 14 May → | |
| mirage | 13–10 | 0.00 | 27% | 13 May → | |
| dust2 | 13–11 | 0.05 | 21% | 13 May → | |
| mirage | 9–13 | 0.04 | 23% | 12 May → | |
| dust2 | 8–13 | 0.03 | 32% | 12 May → | |
| dust2 | 13–9 | 0.06 | 12% | 11 May → | |
| anubis | 13–4 | 0.11 | 27% | 11 May → | |
| vertigo | 8–8 | -0.05 | 21% | 11 May → | |
| inferno | 9–5 | 0.07 | 61% | 11 May → | |
| cache | 13–11 | 0.00 | 24% | 30 Apr → | |
| cache | 13–7 | 0.08 | 30% | 30 Apr → | |
| cache | 13–11 | 0.09 | 26% | 30 Apr → | |
| cache | 13–9 | -0.01 | 29% | 29 Apr → | |
| cache | 5–13 | -0.03 | 19% | 29 Apr → | |
| cache | 13–0 | 0.03 | 17% | 29 Apr → | |
| cache | 6–13 | 0.03 | 20% | 29 Apr → |
Match data via Leetify.