1V4N | easy de fácil — CS2 Stats
ES76561197995865355[U:1:35599627]Steam profile ↗✓ No bans
What changed since last observed
CSDB last observed this profile on 16 Sep 2026 (yesterday). Ranks are recorded once per day this page is viewed.
CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 29 days played since 14 Aug 2026. Come back after the next session and the change shows above.
Is this you? Sign in with Steam to claim it and connect match tracking →
Rating over time
Premier CS Rating
- 475 below peak (19,915)
- +3,712 over 30 days · improving
- Next: Pink band at 20,000 — 560 to go
- Reached: Purple band · Blue band · Light Blue band
Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.
Share this profile
The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +20pp win rate · +0.03 avg rating · −4.1pp headshot accuracy · +60ms reaction
Win rate up 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).
Last 5 · 10 · 20 matches
Last 5
- 4–1 · 80% win rate
- Avg rating 0.06
- Avg headshot accuracy 24%
- Avg reaction 635ms
Last 10
- 7–3 · 70% win rate
- Avg rating 0.05
- Avg headshot accuracy 22%
- Avg reaction 579ms
Last 20
- 12–7–1 · 60% win rate
- Avg rating 0.04
- Avg headshot accuracy 24%
- Avg reaction 549ms
Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.
Player DNA
Primary style: Positional Player — Positioning stands above the rest of this profile (+1.7 against its own average).
Sharp aimerEffective flashesLimited utility dependence
Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.
What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.
Your pro match

Plays most like ZywOo 94% playstyle similarity
Most alike: positioning profile, 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. 64% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
Flashes. 0.87 enemies blinded per flash — utility that consistently lands.
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 7.9/10 (Strong), 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.
Personal bests
Across the last 100 tracked matches.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
| S | 41 | 27–14 | 66% | 0.05 | |
| S | 15 | 11–4 | 73% | 0.05 | |
| C | 14 | 6–8 | 43% | 0.02 | |
| C | 14 | 5–9 | 36% | 0.01 | |
| A | 8 | 5–3 | 63% | 0.05 | |
| D | 6 | 2–4 | 33% | 0.01 | |
| — | 2 | 1–1 | 50% | -0.01 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (33% over 6). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWWLLW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Dust2 | 36 | 69% | 1.25 | 18.3 |
| Inferno | 25 | 64% | 1.06 | 14.8 |
| Mirage | 22 | 45% | 1.00 | 15.8 |
| Ancient | 11 | 55% | 0.91 | 15.4 |
| Nuke | 11 | 64% | 1.41 | 20.3 |
| Overpass | 9 | 44% | 1.17 | 15.9 |
| Anubis | 5 | 40% | 1.09 | 15.6 |
| Train | 1 | 100% | 0.69 | 11.0 |
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.
- Grenades & UtilityGrenade Lineups →
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 3.9922 — below the 4 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 6 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 5–13 | -0.05 | 39% | 17 Sept → | ||
| 13–7 | 0.01 | 21% | 16 Sept → | ||
| 13–7 | 0.10 | 29% | 16 Sept → | ||
| 13–3 | 0.09 | 18% | 15 Sept → | ||
| 13–6 | 0.15 | 15% | 15 Sept → | ||
| 8–13 | 0.03 | 23% | 15 Sept → | ||
| 13–6 | 0.10 | 20% | 15 Sept → | ||
| 13–6 | 0.12 | 19% | 13 Sept → | ||
| 13–9 | -0.01 | 20% | 13 Sept → | ||
| 7–13 | 0.01 | 19% | 13 Sept → | ||
| 15–15 | 0.01 | 17% | 13 Sept → | ||
| 10–13 | 0.05 | 20% | 13 Sept → | ||
| 13–8 | 0.06 | 33% | 11 Sept → | ||
| 9–13 | -0.01 | 20% | 11 Sept → | ||
| 13–11 | 0.02 | 29% | 10 Sept → | ||
| 13–11 | 0.01 | 21% | 10 Sept → | ||
| 7–13 | -0.05 | 35% | 10 Sept → | ||
| 13–4 | 0.04 | 41% | 9 Sept → | ||
| 13–9 | 0.05 | 21% | 9 Sept → | ||
| 14–16 | 0.03 | 26% | 9 Sept → | ||
| 13–8 | 0.07 | 25% | 9 Sept → | ||
| 9–13 | -0.01 | 34% | 9 Sept → | ||
| 13–7 | 0.08 | 37% | 8 Sept → | ||
| 6–13 | -0.01 | 30% | 8 Sept → | ||
| 2–13 | -0.00 | 80% | 8 Sept → | ||
| 15–15 | 0.08 | 23% | 8 Sept → | ||
| 13–11 | -0.04 | 25% | 7 Sept → | ||
| 8–13 | -0.02 | 13% | 7 Sept → | ||
| 6–13 | -0.02 | 23% | 7 Sept → | ||
| 13–9 | 0.11 | 26% | 4 Sept → | ||
| 13–16 | -0.04 | 24% | 4 Sept → | ||
| 7–12 | 0.12 | 26% | 4 Sept → | ||
| 15–15 | 0.06 | 20% | 3 Sept → | ||
| 13–11 | 0.11 | 29% | 3 Sept → | ||
| 13–0 | 0.02 | 33% | 3 Sept → | ||
| 13–0 | 0.07 | 26% | 3 Sept → | ||
| 11–13 | 0.05 | 21% | 3 Sept → | ||
| 13–9 | 0.02 | 26% | 3 Sept → | ||
| 16–14 | 0.02 | 22% | 2 Sept → | ||
| 13–10 | 0.07 | 19% | 2 Sept → | ||
| 5–13 | -0.00 | 28% | 2 Sept → | ||
| 13–5 | 0.01 | 21% | 1 Sept → | ||
| 13–10 | 0.01 | 19% | 1 Sept → | ||
| 9–13 | -0.00 | 16% | 1 Sept → | ||
| 0–13 | -0.16 | 25% | 1 Sept → | ||
| 4–13 | -0.02 | 19% | 1 Sept → | ||
| 16–14 | 0.02 | 16% | 31 Aug → | ||
| 11–13 | 0.04 | 17% | 31 Aug → | ||
| 15–15 | 0.01 | 19% | 31 Aug → | ||
| 13–11 | 0.02 | 23% | 29 Aug → | ||
| 13–9 | 0.05 | 14% | 29 Aug → | ||
| 16–14 | 0.09 | 31% | 29 Aug → | ||
| 13–0 | 0.08 | 4% | 29 Aug → | ||
| 13–2 | 0.03 | 30% | 29 Aug → | ||
| 9–13 | -0.02 | 16% | 28 Aug → | ||
| 13–5 | -0.00 | 25% | 28 Aug → | ||
| 13–8 | 0.09 | 27% | 28 Aug → | ||
| 9–13 | 0.12 | 24% | 28 Aug → | ||
| 13–2 | 0.02 | 26% | 27 Aug → | ||
| 13–9 | 0.04 | 23% | 27 Aug → | ||
| 13–7 | 0.06 | 43% | 27 Aug → | ||
| 11–13 | 0.13 | 26% | 27 Aug → | ||
| 13–8 | 0.06 | 30% | 26 Aug → | ||
| 15–15 | 0.02 | 26% | 26 Aug → | ||
| 13–8 | 0.13 | 35% | 26 Aug → | ||
| 13–5 | -0.04 | 18% | 26 Aug → | ||
| 13–8 | 0.08 | 32% | 25 Aug → | ||
| 13–1 | 0.10 | 45% | 25 Aug → | ||
| 13–2 | 0.10 | 58% | 25 Aug → | ||
| 10–13 | -0.00 | 24% | 24 Aug → | ||
| 13–11 | 0.02 | 24% | 24 Aug → | ||
| 11–13 | -0.05 | 23% | 24 Aug → | ||
| 7–13 | 0.06 | 21% | 24 Aug → | ||
| 10–13 | 0.07 | 23% | 23 Aug → | ||
| 9–13 | 0.02 | 20% | 23 Aug → | ||
| 13–5 | 0.14 | 26% | 23 Aug → | ||
| 13–5 | 0.02 | 18% | 23 Aug → | ||
| 13–11 | 0.05 | 22% | 22 Aug → | ||
| 11–13 | 0.09 | 26% | 21 Aug → | ||
| 6–13 | -0.07 | 24% | 21 Aug → | ||
| 13–4 | 0.10 | 20% | 21 Aug → | ||
| 2–13 | -0.04 | 25% | 21 Aug → | ||
| 9–13 | -0.02 | 29% | 21 Aug → | ||
| 11–13 | -0.05 | 25% | 20 Aug → | ||
| 13–6 | -0.02 | 24% | 19 Aug → | ||
| 13–3 | 0.04 | 27% | 19 Aug → | ||
| 13–2 | 0.07 | 19% | 19 Aug → | ||
| 13–11 | 0.03 | 14% | 19 Aug → | ||
| 13–10 | 0.03 | 22% | 18 Aug → | ||
| 13–3 | 0.05 | 25% | 18 Aug → | ||
| 10–13 | 0.04 | 21% | 18 Aug → | ||
| 10–13 | 0.08 | 19% | 18 Aug → | ||
| 10–13 | -0.02 | 32% | 17 Aug → | ||
| 14–16 | 0.07 | 26% | 17 Aug → | ||
| 13–7 | -0.01 | 16% | 16 Aug → | ||
| 4–13 | 0.02 | 26% | 14 Aug → | ||
| 13–4 | 0.07 | 38% | 14 Aug → | ||
| 13–7 | 0.07 | 22% | 14 Aug → | ||
| 13–6 | 0.19 | 17% | 14 Aug → | ||
| 13–10 | 0.06 | 27% | 14 Aug → |
Match data via Leetify.