aragornN — CS2 Stats
PROBC.GamePortugalRiflerSettings & gear profile →
76561198804877596[U:1:844611868]
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -10pp win rate · -0.05 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
Sharp aimerStrong CT-side openerEffective flashesHigh utility contribution
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, positioning profile.
Where you differ: higher 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 91 — 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.
Utility. Utility score of 80 — grenade impact well above the norm.
Areas to improve
T-side openings. Opening success drops from 67% on CT to 41% on T — the same duels are being taken with worse setups on the attacking side.
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 8.7/10 (Elite), a weighted mean of the bars with a small opposition adjustment (×1.05 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 |
|---|---|---|---|---|---|
| S | 19 | 16–3 | 84% | 0.08 | |
| B | 19 | 10–9 | 53% | 0.03 | |
| A | 18 | 10–8 | 56% | 0.04 | |
| A | 11 | 6–5 | 55% | 0.03 | |
| C | 9 | 4–5 | 44% | 0.03 | |
| S | 8 | 6–2 | 75% | 0.01 | |
| S | 7 | 6–1 | 86% | 0.03 | |
| S | 7 | 6–1 | 86% | 0.06 | |
| office | — | 1 | 1–0 | 100% | 0.08 |
| — | 1 | 1–0 | 100% | 0.15 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (44% over 9). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWLWWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Ancient | 540 | 67% | 1.55 | 20.2 |
| Dust2 | 393 | 67% | 1.56 | 21.1 |
| Anubis | 360 | 61% | 1.30 | 18.3 |
| Mirage | 262 | 64% | 1.70 | 22.7 |
| Inferno | 148 | 65% | 1.41 | 18.3 |
| Vertigo | 90 | 72% | 1.30 | 18.7 |
| Nuke | 57 | 61% | 1.44 | 20.6 |
| Train | 45 | 67% | 1.41 | 18.8 |
Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.
Inventory
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
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
44% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 16–13 | 0.08 | 21% | 15 Aug → | ||
| 13–6 | 0.13 | 23% | 13 Aug → | ||
| 4–13 | -0.01 | 21% | 11 Aug → | ||
| 14–16 | 0.01 | 16% | 11 Aug → | ||
| 13–4 | 0.06 | 24% | 7 Aug → | ||
| 13–9 | 0.09 | 26% | 5 Aug → | ||
| 13–10 | 0.02 | 25% | 4 Aug → | ||
| 13–6 | 0.12 | 22% | 31 Jul → | ||
| 13–7 | 0.09 | 25% | 28 Jul → | ||
| 6–13 | -0.06 | 9% | 23 Jul → | ||
| 13–10 | 0.12 | 27% | 18 Jul → | ||
| 16–14 | 0.09 | 22% | 16 Jul → | ||
| 8–13 | 0.09 | 34% | 16 Jul → | ||
| 13–2 | 0.05 | 22% | 14 Jul → | ||
| 13–10 | 0.08 | 20% | 12 Jul → | ||
| 13–10 | 0.12 | 23% | 11 Jul → | ||
| 13–1 | 0.23 | 22% | 9 Jul → | ||
| 13–2 | 0.18 | 31% | 9 Jul → | ||
| 13–10 | 0.07 | 18% | 8 Jul → | ||
| 12–12 | 0.01 | 20% | 6 Jul → | ||
| 13–6 | 0.14 | 22% | 6 Jul → | ||
| 13–6 | 0.20 | 17% | 4 Jul → | ||
| 13–9 | 0.03 | 15% | 14 Jun → | ||
| 6–13 | -0.02 | 29% | 8 Jun → | ||
| 6–13 | -0.03 | 40% | 8 Jun → | ||
| 13–6 | 0.02 | 32% | 7 Jun → | ||
| 13–11 | 0.07 | 25% | 6 Jun → | ||
| 13–3 | 0.11 | 35% | 29 May → | ||
| 13–9 | 0.03 | 31% | 19 May → | ||
| office | 13–10 | 0.08 | 32% | 15 May → | |
| 13–9 | 0.07 | 35% | 12 May → | ||
| 13–11 | -0.03 | 24% | 11 May → | ||
| 4–13 | 0.08 | 20% | 11 May → | ||
| 13–9 | 0.10 | 20% | 10 May → | ||
| 12–12 | 0.02 | 30% | 6 May → | ||
| 7–2 | 0.09 | 29% | 6 May → | ||
| 13–5 | 0.12 | 21% | 6 May → | ||
| 19–15 | 0.06 | 16% | 6 May → | ||
| 13–9 | 0.05 | 29% | 30 Apr → | ||
| 6–0 | -0.01 | 50% | 30 Apr → | ||
| 13–11 | 0.02 | 25% | 30 Apr → | ||
| 13–10 | 0.15 | 34% | 23 Apr → | ||
| 13–5 | 0.06 | 11% | 22 Apr → | ||
| 13–8 | 0.07 | 15% | 21 Apr → | ||
| 13–9 | 0.01 | 28% | 21 Apr → | ||
| 13–11 | -0.02 | 32% | 18 Apr → | ||
| 11–13 | 0.16 | 25% | 17 Apr → | ||
| 13–10 | 0.11 | 23% | 16 Apr → | ||
| 13–8 | 0.14 | 26% | 10 Apr → | ||
| 1–12 | -0.01 | 33% | 8 Apr → | ||
| 10–13 | -0.03 | 10% | 7 Apr → | ||
| 3–13 | -0.04 | 18% | 7 Apr → | ||
| 10–13 | -0.09 | 10% | 6 Apr → | ||
| 13–9 | 0.02 | 10% | 6 Apr → | ||
| 13–4 | 0.02 | 10% | 6 Apr → | ||
| 11–13 | -0.07 | 14% | 5 Apr → | ||
| 10–13 | -0.01 | 17% | 5 Apr → | ||
| 13–11 | -0.03 | 12% | 5 Apr → | ||
| 3–13 | -0.04 | 14% | 4 Apr → | ||
| 11–13 | 0.01 | 16% | 4 Apr → | ||
| 10–13 | -0.04 | 12% | 3 Apr → | ||
| 13–7 | -0.04 | 22% | 3 Apr → | ||
| 13–9 | 0.06 | 26% | 1 Apr → | ||
| 7–9 | -0.01 | 20% | 30 Mar → | ||
| 13–7 | 0.08 | 23% | 28 Mar → | ||
| 13–6 | -0.02 | 19% | 28 Mar → | ||
| 13–2 | 0.12 | 24% | 28 Mar → | ||
| 13–7 | -0.03 | 10% | 28 Mar → | ||
| 10–13 | 0.07 | 31% | 26 Mar → | ||
| 13–1 | 0.09 | 33% | 26 Mar → | ||
| 17–19 | 0.06 | 17% | 25 Mar → | ||
| 13–16 | 0.08 | 24% | 24 Mar → | ||
| 13–7 | 0.03 | 23% | 23 Mar → | ||
| 13–10 | 0.07 | 23% | 20 Mar → | ||
| 6–13 | 0.05 | 40% | 20 Mar → | ||
| 9–5 | 0.14 | 24% | 18 Mar → | ||
| 13–8 | 0.05 | 20% | 16 Mar → | ||
| 11–13 | -0.06 | 24% | 14 Mar → | ||
| 5–13 | -0.02 | 20% | 13 Mar → | ||
| 13–11 | 0.09 | 27% | 6 Mar → | ||
| 13–8 | 0.06 | 22% | 6 Mar → | ||
| 13–10 | 0.05 | 15% | 5 Mar → | ||
| 13–5 | 0.08 | 25% | 5 Mar → | ||
| 10–13 | -0.01 | 20% | 4 Mar → | ||
| 15–15 | 0.05 | 26% | 27 Feb → | ||
| 13–4 | 0.07 | 31% | 27 Feb → | ||
| 13–9 | -0.00 | 32% | 27 Feb → | ||
| 13–4 | 0.07 | 13% | 26 Feb → | ||
| 13–10 | -0.01 | 18% | 26 Feb → | ||
| 13–4 | 0.08 | 16% | 25 Feb → | ||
| 9–13 | -0.04 | 32% | 23 Feb → | ||
| 2–13 | -0.07 | 29% | 23 Feb → | ||
| 9–13 | -0.04 | 32% | 23 Feb → | ||
| 2–13 | -0.07 | 29% | 23 Feb → | ||
| 13–7 | 0.02 | 15% | 23 Feb → | ||
| 13–8 | 0.01 | 21% | 23 Feb → | ||
| 13–7 | 0.02 | 15% | 23 Feb → | ||
| 13–8 | 0.01 | 21% | 23 Feb → | ||
| 13–16 | 0.00 | 25% | 23 Feb → | ||
| 5–13 | -0.05 | 13% | 23 Feb → |
Match data via Leetify.
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