ElQulo — CS2 Stats

FO76561199152719851[U:1:1192454123]Steam profile ↗✓ No bans

1,008Tracked matches33%Win rate2021Tracked since

CSDB Rating5.8 SolidAggressive Rifler

Premier CS Rating11,258Blue band · top ~48.2% of ranked players (population est.)

CSDB Leaderboard#42089 of 60492 tracked

FaceitLevel 3Top 90.6% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim79

Positioning59

Utility66

0–100 skill scores via Leetify.

Recent form

COLD50–50Last 10050%Win rateLLWLLLWLLL

Last 10 vs previous 10: -20pp win rate · +0.01 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim7.9

Aggression7.9

Utility6.6

Positioning5.9

Opening Duels2.8

Clutch4.4

Effective flashes

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 91% playstyle similarity

Most alike: opening-duel success, utility contribution.

Where you differ: lower aim profile; higher opening-fight frequency.

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

Flashes. 0.84 enemies blinded per flash — utility that consistently lands.

Areas to improve

Reaction time. 656ms 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

Aim7.9

Positioning5.9

Utility6.6

Mechanics8.3

Opening Duels2.8

Win Impact0.0

Composite 5.8/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.02

first ⅓ avg 0.01 → last ⅓ avg -0.01

Reaction time659ms−10ms

first ⅓ avg 669ms → last ⅓ avg 659ms

Headshot accuracy14.4%−0.7%

first ⅓ avg 15.0% → last ⅓ avg 14.4%

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

0.15Best rating — mirage 13–10

13–0Biggest win — overpass

5Longest win streak

L2Current streak

9–11In matches decided by ≤2 rounds

10Overtime games

Map breakdown

dust2Best map · 58% over 43infernoWeakest map · 33% over 15

Map	Grade	Played	Record	Win rate	Avg rating
dust2	A	43	25–18	58%	0.00
inferno	D	15	5–10	33%	-0.03
mirage	B	15	7–8	47%	0.01
anubis	B	8	4–4	50%	-0.01
nuke	B	6	3–3	50%	0.01
cache	D	6	2–4	33%	-0.02
ancient	C	5	2–3	40%	-0.01
overpass	—	2	2–0	100%	0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 15). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

499Matches

49%Win rate

1.02Avg K/D

78.3ADR

32%Headshot %

Clutches & streaks

42%1v1 clutch win

26%1v2 clutch win

7Longest win streak

Recent Faceit resultsLLLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	73	47%	1.02	14.7
Dust2	57	54%	1.07	16.2
Inferno	56	43%	0.90	14.5
Ancient	50	56%	1.07	15.9
Anubis	35	57%	1.04	14.6
Nuke	15	47%	1.14	16.5
Vertigo	4	0%	0.68	11.5
Cache	1	100%	1.00	17.0

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.

14.9%Headshot accuracy

40.4%Accuracy (enemy spotted)

44.9%Spray accuracy

87.3%Counter-strafing

9.7°Preaim

656msReaction time

36.5%T opening success

46.0%CT opening success

0.84Enemies flashed / flash

5.1%Flash assists

13.48HE damage / grenade

9.17Flashes / 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 14.8626% — 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 36.4583% — below the 40% mark we flag

Spend your practice time on Inferno

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 15 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
ancient	14–16	0.03	19%	29 Aug →
nuke	8–13	0.03	11%	29 Aug →
dust2	13–5	0.02	15%	26 Aug →
inferno	14–16	0.05	22%	23 Aug →
dust2	13–16	0.04	14%	23 Aug →
cache	0–13	-0.08	12%	23 Aug →
dust2	13–11	0.03	20%	23 Aug →
inferno	14–16	-0.02	14%	22 Aug →
anubis	8–13	-0.04	13%	22 Aug →
dust2	4–13	-0.05	15%	22 Aug →
mirage	8–13	0.02	17%	22 Aug →
dust2	4–13	-0.09	13%	15 Aug →
dust2	13–10	0.03	18%	15 Aug →
inferno	9–13	-0.04	8%	15 Aug →
cache	4–13	-0.03	19%	15 Aug →
inferno	8–13	-0.02	12%	15 Aug →
dust2	13–8	0.02	23%	15 Aug →
inferno	13–4	-0.03	8%	15 Aug →
mirage	11–13	0.08	7%	14 Aug →
dust2	13–7	-0.00	15%	14 Aug →
dust2	9–13	0.01	20%	14 Aug →
mirage	13–11	-0.07	14%	14 Aug →
ancient	0–13	-0.09	10%	14 Aug →
dust2	11–13	-0.04	23%	13 Aug →
dust2	7–13	0.05	10%	13 Aug →
dust2	13–10	0.01	9%	13 Aug →
dust2	5–13	-0.07	11%	13 Aug →
dust2	13–10	0.07	13%	13 Aug →
nuke	13–6	0.03	19%	13 Aug →
dust2	2–13	-0.03	13%	13 Aug →
mirage	1–13	-0.05	15%	13 Aug →
dust2	6–13	-0.05	7%	12 Aug →
anubis	13–7	-0.02	17%	12 Aug →
inferno	6–13	-0.08	15%	12 Aug →
inferno	9–13	-0.05	10%	12 Aug →
dust2	13–9	-0.05	9%	11 Aug →
dust2	13–10	-0.06	12%	11 Aug →
dust2	13–9	-0.02	10%	11 Aug →
anubis	13–10	-0.04	15%	11 Aug →
mirage	13–16	-0.00	14%	10 Aug →
cache	13–11	-0.02	13%	10 Aug →
mirage	13–10	-0.01	11%	10 Aug →
inferno	10–13	-0.10	13%	10 Aug →
dust2	13–10	0.06	11%	10 Aug →
mirage	13–3	0.05	25%	3 Aug →
anubis	13–9	0.02	19%	3 Aug →
anubis	11–13	0.04	8%	3 Aug →
dust2	13–5	0.05	21%	2 Aug →
nuke	8–13	0.06	15%	2 Aug →
dust2	10–13	-0.03	14%	31 Jul →
dust2	14–16	-0.06	10%	30 Jul →
ancient	0–4	-0.04	40%	30 Jul →
mirage	11–13	-0.01	14%	30 Jul →
ancient	13–4	0.03	11%	30 Jul →
dust2	13–11	-0.01	22%	27 Jul →
mirage	13–8	0.03	13%	23 Jul →
mirage	14–16	0.01	17%	19 Jul →
cache	13–8	0.04	7%	19 Jul →
mirage	13–3	-0.00	12%	19 Jul →
inferno	9–13	-0.05	8%	17 Jul →
cache	5–13	-0.04	5%	17 Jul →
anubis	5–13	-0.06	15%	17 Jul →
cache	6–13	-0.02	10%	17 Jul →
inferno	13–5	0.03	13%	17 Jul →
dust2	8–13	0.03	6%	17 Jul →
dust2	16–14	0.02	17%	14 Jul →
nuke	16–14	-0.03	11%	3 Jul →
dust2	8–13	-0.03	22%	26 Jun →
dust2	13–9	0.07	26%	26 Jun →
inferno	7–9	-0.09	10%	11 Jun →
inferno	4–9	-0.17	27%	11 Jun →
nuke	10–13	0.00	15%	11 Jun →
inferno	13–4	0.08	16%	7 Jun →
mirage	13–10	0.15	11%	7 Jun →
dust2	13–8	0.06	8%	7 Jun →
dust2	13–7	0.05	9%	6 Jun →
mirage	8–13	-0.03	13%	6 Jun →
anubis	13–11	0.03	14%	5 Jun →
dust2	13–10	0.01	21%	5 Jun →
nuke	13–8	-0.02	11%	5 Jun →
dust2	13–3	0.11	16%	5 Jun →
mirage	10–13	-0.06	9%	4 Jun →
mirage	13–10	-0.01	13%	4 Jun →
anubis	11–13	-0.02	8%	4 Jun →
dust2	6–13	0.02	10%	4 Jun →
overpass	13–0	-0.01	11%	30 May →
dust2	6–13	-0.05	14%	30 May →
dust2	13–8	0.02	20%	30 May →
dust2	13–6	-0.03	23%	23 May →
dust2	12–16	0.04	15%	16 May →
inferno	13–6	0.01	10%	16 May →
dust2	13–3	0.05	21%	16 May →
inferno	13–8	-0.01	19%	16 May →
dust2	6–13	-0.04	15%	16 May →
dust2	5–13	-0.03	28%	15 May →
dust2	13–10	-0.04	15%	8 May →
ancient	13–11	0.00	11%	8 May →
overpass	13–6	0.10	17%	24 Apr →
dust2	13–11	0.04	8%	24 Apr →
dust2	13–6	0.00	13%	24 Apr →