-viejo- — CS2 Stats

NO76561197976734568[U:1:16468840]Steam profile ↗✓ No bans

2,475Tracked matches43%Win rate2020Tracked since

CSDB Rating4.4 Developing

Premier CS Rating17,885Purple band · top ~16.9% of ranked players (population est.)

CSDB Leaderboard#27152 of 55609 tracked

FaceitLevel 8 · 1,330 ELOTop 31.2% of ranked FACEIT players

WingmanLegendary Eagle

Ladder ranks via Leetify

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Performance scores

Aim47

Positioning43

Utility64

0–100 skill scores via Leetify.

Recent form

COLD44–53–3Last 10044%Win rateLWLWLWLLLL

Last 10 vs previous 10: +10pp win rate · -0.00 avg rating

Player DNA

Aim4.7

Aggression4.0

Utility6.4

Positioning4.3

Opening Duels0.2

Clutch3.0

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 79% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

Where you differ: lower opening-duel success; 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. 622ms 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

Aim4.7

Positioning4.3

Utility6.4

Mechanics5.5

Opening Duels0.4

Win Impact2.6

Composite 4.4/10 (Developing), 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

Match rating-0.02−0.01

first ⅓ avg -0.01 → last ⅓ avg -0.02

Reaction time641ms+55ms

first ⅓ avg 586ms → last ⅓ avg 641ms

Headshot accuracy15.1%−1.9%

first ⅓ avg 17.0% → last ⅓ avg 15.1%

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

0.11Best rating — anubis 13–1

13–1Biggest win — mirage

5Longest win streak

2–12In matches decided by ≤2 rounds

8Overtime games

Map breakdown

mirageBest map · 56% over 9dust2Weakest map · 18% over 11

Map	Grade	Played	Record	Win rate	Avg rating
inferno	C	31	12–19	39%	-0.03
anubis	A	20	11–9	55%	-0.01
ancient	B	13	6–7	46%	-0.00
nuke	B	12	6–6	50%	0.02
dust2	D	11	2–9	18%	-0.02
mirage	A	9	5–4	56%	-0.04
overpass	—	3	1–2	33%	-0.01
cache	—	1	1–0	100%	-0.06

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (18% over 11). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

2,618Matches

50%Win rate

1.04Avg K/D

75.6ADR

36%Headshot %

Clutches & streaks

35%1v1 clutch win

19%1v2 clutch win

11Longest win streak

Recent Faceit resultsWLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	273	52%	1.09	14.7
Anubis	223	55%	1.05	15.2
Ancient	202	50%	1.04	15.2
Mirage	123	46%	1.02	14.8
Nuke	67	51%	1.03	15.6
Dust2	59	46%	0.88	13.1
Vertigo	50	50%	0.97	14.5
Overpass	25	32%	0.87	12.9

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.

13.9%Headshot accuracy

32.8%Accuracy (enemy spotted)

33.4%Spray accuracy

74.7%Counter-strafing

11.0°Preaim

622msReaction time

32.8%T opening success

28.8%CT opening success

0.57Enemies flashed / flash

7.6%Flash assists

11.87HE damage / grenade

12.07Flashes / match

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 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 13.8845% — below the 15% mark we flag
Aim Training →
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 32.8391% — below the 40% mark we flag

Spend your practice time on Dust 2

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

18% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
anubis	7–13	-0.08	12%	29 Aug →
cache	13–10	-0.06	3%	21 Aug →
dust2	2–13	-0.05	13%	21 Aug →
nuke	13–8	0.05	9%	21 Aug →
ancient	10–13	-0.02	12%	16 Aug →
inferno	13–6	0.05	20%	16 Aug →
inferno	6–13	-0.03	14%	16 Aug →
inferno	11–13	-0.04	11%	14 Aug →
dust2	10–13	-0.07	27%	14 Aug →
anubis	4–13	-0.07	5%	14 Aug →
inferno	3–9	-0.16	21%	14 Aug →
inferno	8–8	-0.03	17%	14 Aug →
inferno	11–13	-0.04	9%	13 Aug →
dust2	15–15	0.02	10%	13 Aug →
anubis	13–10	0.02	14%	13 Aug →
inferno	2–9	0.02	33%	13 Aug →
inferno	9–2	-0.00	25%	13 Aug →
dust2	11–13	-0.05	8%	11 Aug →
anubis	6–13	-0.04	16%	11 Aug →
inferno	8–13	-0.04	13%	11 Aug →
anubis	13–8	0.03	9%	3 Aug →
nuke	13–7	0.08	24%	3 Aug →
inferno	13–9	0.01	22%	2 Aug →
ancient	13–8	0.05	18%	2 Aug →
mirage	0–10	-0.08	33%	28 Jul →
ancient	13–4	0.05	9%	28 Jul →
inferno	13–8	-0.03	8%	28 Jul →
ancient	13–3	0.07	17%	28 Jul →
dust2	13–10	-0.05	22%	28 Jul →
nuke	15–15	0.01	16%	28 Jul →
inferno	9–13	0.00	5%	24 Jul →
anubis	11–13	-0.01	14%	24 Jul →
inferno	3–13	-0.08	10%	18 Jul →
anubis	9–13	-0.06	29%	18 Jul →
mirage	13–7	0.02	7%	18 Jul →
ancient	11–13	-0.04	5%	18 Jul →
inferno	16–14	0.06	12%	3 Jul →
inferno	13–4	-0.04	26%	25 Jun →
ancient	5–5	0.06	8%	25 Jun →
nuke	11–13	0.02	13%	25 Jun →
anubis	13–8	-0.05	17%	13 Jun →
anubis	13–16	0.01	19%	13 Jun →
nuke	6–13	-0.04	20%	13 Jun →
inferno	13–5	-0.03	11%	13 Jun →
dust2	3–8	0.00	0%	29 May →
mirage	13–9	-0.00	10%	23 May →
ancient	8–13	0.02	20%	23 May →
dust2	8–13	-0.01	24%	23 May →
inferno	11–13	-0.07	14%	16 May →
ancient	11–13	-0.07	16%	16 May →
dust2	9–13	-0.02	8%	16 May →
inferno	6–13	-0.02	9%	14 May →
mirage	4–13	-0.02	15%	14 May →
dust2	8–13	0.01	17%	14 May →
anubis	13–11	0.03	18%	14 May →
inferno	9–13	-0.01	14%	14 May →
nuke	13–8	0.02	28%	14 May →
anubis	13–9	-0.01	15%	14 May →
ancient	13–8	0.02	17%	14 May →
mirage	3–5	-0.12	33%	12 May →
inferno	10–13	-0.03	28%	12 May →
overpass	13–2	-0.01	4%	12 May →
dust2	2–13	-0.07	25%	12 May →
overpass	10–13	0.02	19%	9 May →
ancient	13–9	-0.04	9%	9 May →
inferno	13–6	0.02	15%	9 May →
ancient	8–13	-0.05	10%	8 May →
mirage	8–13	-0.07	15%	8 May →
inferno	3–13	-0.10	30%	7 May →
nuke	13–5	0.03	21%	7 May →
overpass	3–13	-0.05	19%	3 May →
nuke	13–5	0.02	16%	3 May →
anubis	9–13	-0.06	8%	3 May →
inferno	13–10	-0.03	25%	3 May →
mirage	13–1	-0.04	14%	3 May →
ancient	13–8	0.02	20%	2 May →
inferno	16–12	-0.03	14%	2 May →
anubis	13–5	0.09	16%	2 May →
inferno	12–16	-0.05	13%	2 May →
nuke	7–13	0.01	15%	2 May →
anubis	13–7	-0.01	21%	30 Apr →
anubis	13–6	0.04	13%	28 Apr →
inferno	13–6	0.02	19%	28 Apr →
anubis	13–7	-0.05	23%	28 Apr →
nuke	9–13	-0.03	8%	28 Apr →
inferno	11–13	-0.00	11%	26 Apr →
inferno	5–13	-0.11	0%	25 Apr →
anubis	10–13	-0.05	24%	25 Apr →
inferno	12–16	-0.01	24%	25 Apr →
inferno	12–16	-0.01	24%	25 Apr →
anubis	13–3	0.04	16%	25 Apr →
nuke	8–13	0.00	16%	25 Apr →
nuke	13–8	0.03	23%	23 Apr →
anubis	13–1	0.11	20%	23 Apr →
inferno	13–10	0.02	13%	23 Apr →
ancient	3–13	-0.08	10%	23 Apr →
mirage	13–5	-0.02	10%	23 Apr →
anubis	11–13	-0.01	11%	22 Apr →
mirage	13–9	-0.02	11%	22 Apr →
dust2	13–5	0.08	38%	21 Apr →