El Capitano — CS2 Stats

DE76561198386735348[U:1:426469620]Steam profile ↗

772Tracked matches52%Win rate2021Tracked since

CSDB Rating5.3 DevelopingHybrid Rifler

WingmanSilver Elite Master

Ladder ranks via Leetify

Performance scores

Aim69

Positioning48

Utility25

0–100 skill scores via Leetify.

Recent form

STEADY50–45–5Last 10050%Win rateLWWLWLWWWL

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

Player DNA

Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.

Aim6.9

Aggression6.6

Utility2.5

Positioning4.8

Opening Duels2.9

Clutch6.0

Limited 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.

Your pro match

Plays most like ropz 83% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

Where you differ: lower utility contribution; 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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 659ms 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

Aim6.9

Positioning4.8

Utility2.5

Mechanics6.8

Opening Duels2.9

Win Impact5.6

Composite 5.3/10 (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 rating0.01−0.00

first ⅓ avg 0.01 → last ⅓ avg 0.01

Reaction time660ms−33ms

first ⅓ avg 693ms → last ⅓ avg 660ms

Headshot accuracy22.0%+1.1%

first ⅓ avg 20.9% → last ⅓ avg 22.0%

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 — dust2 7–7

13–0Biggest win — dust2

4Longest win streak

6–9In matches decided by ≤2 rounds

Map breakdown

dust2Best map · 70% over 10trainWeakest map · 33% over 6

Map	Grade	Played	Record	Win rate	Avg rating
inferno	C	32	14–18	44%	0.00
mirage	C	19	8–11	42%	0.01
anubis	A	16	10–6	63%	0.03
vertigo	A	12	7–5	58%	0.03
dust2	S	10	7–3	70%	0.04
train	D	6	2–4	33%	0.04
cache	—	3	2–1	67%	-0.02
overpass	—	2	0–2	0%	0.02

Across the last 100 tracked matches.

Faceit stats

Combat

8Matches

50%Win rate

0.83Avg K/D

77.7ADR

44%Headshot %

Clutches & streaks

50%1v1 clutch win

60%1v2 clutch win

1Longest win streak

Recent Faceit resultsWLWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	3	33%	0.96	13.7
Anubis	2	100%	0.86	20.0
Train	2	0%	0.80	17.0
Ancient	1	100%	0.44	8.0

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.

22.0%Headshot accuracy

36.5%Accuracy (enemy spotted)

40.2%Spray accuracy

80.5%Counter-strafing

11.3°Preaim

659msReaction time

34.6%T opening success

48.5%CT opening success

0.38Enemies flashed / flash

2.3%Flash assists

10.00HE damage / grenade

1.70Flashes / 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.

Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.3813 — below the 0.5 mark we flag
Grenade Lineups →
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 34.586% — below the 40% mark we flag

Spend your practice time on Train

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.

Train callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
inferno	10–13	-0.02	22%	28 Aug →
dust2	7–7	0.15	11%	28 Aug →
mirage	13–2	0.08	27%	28 Aug →
inferno	8–13	-0.00	13%	28 Aug →
inferno	13–8	0.05	21%	26 Aug →
mirage	5–13	0.03	28%	24 Aug →
anubis	13–7	0.04	37%	24 Aug →
anubis	13–7	0.02	18%	23 Aug →
inferno	13–7	-0.01	25%	23 Aug →
inferno	11–13	-0.05	20%	23 Aug →
mirage	12–12	0.01	31%	22 Aug →
mirage	13–4	-0.00	11%	19 Aug →
inferno	13–7	0.07	12%	19 Aug →
cache	13–11	0.09	23%	15 Aug →
mirage	1–13	-0.07	0%	15 Aug →
mirage	7–9	0.13	28%	15 Aug →
inferno	7–13	-0.06	18%	13 Aug →
mirage	8–13	-0.01	25%	13 Aug →
train	7–13	-0.00	30%	11 Aug →
mirage	10–13	0.04	24%	11 Aug →
inferno	9–13	-0.05	23%	9 Aug →
mirage	9–13	-0.01	12%	8 Aug →
inferno	6–13	-0.06	35%	7 Aug →
anubis	13–8	0.02	30%	7 Aug →
vertigo	13–9	0.08	24%	5 Aug →
inferno	11–13	0.02	19%	4 Aug →
mirage	13–9	-0.07	23%	2 Aug →
inferno	13–2	0.04	27%	2 Aug →
cache	4–13	-0.07	10%	2 Aug →
dust2	13–7	-0.00	23%	1 Aug →
mirage	13–9	0.06	26%	31 Jul →
dust2	6–13	-0.02	26%	31 Jul →
overpass	11–13	-0.06	23%	30 Jul →
vertigo	10–13	0.06	21%	30 Jul →
vertigo	12–1	0.14	22%	30 Jul →
vertigo	13–4	0.12	27%	28 Jul →
dust2	13–10	0.10	31%	26 Jul →
anubis	0–13	-0.03	20%	26 Jul →
train	13–3	0.08	21%	26 Jul →
vertigo	13–9	0.01	35%	25 Jul →
anubis	13–8	0.02	18%	25 Jul →
inferno	13–7	0.10	29%	25 Jul →
inferno	7–13	0.01	20%	25 Jul →
vertigo	13–3	-0.01	21%	24 Jul →
dust2	13–4	0.03	17%	24 Jul →
vertigo	12–12	-0.06	10%	24 Jul →
anubis	6–13	0.06	36%	24 Jul →
anubis	13–4	0.04	18%	24 Jul →
mirage	13–7	0.05	18%	24 Jul →
dust2	6–13	-0.05	25%	23 Jul →
inferno	4–13	0.05	17%	23 Jul →
dust2	12–12	-0.07	31%	23 Jul →
inferno	5–9	-0.08	28%	23 Jul →
inferno	9–0	0.08	50%	23 Jul →
mirage	13–5	-0.09	35%	21 Jul →
dust2	13–0	0.07	24%	21 Jul →
dust2	13–6	0.10	32%	21 Jul →
anubis	9–13	0.05	19%	20 Jul →
inferno	13–9	-0.01	24%	19 Jul →
anubis	13–11	0.06	26%	19 Jul →
inferno	13–1	-0.05	13%	19 Jul →
overpass	11–13	0.10	20%	19 Jul →
mirage	9–13	0.05	22%	19 Jul →
inferno	13–8	0.01	13%	18 Jul →
cache	2–0	-0.06	10%	18 Jul →
inferno	4–5	-0.01	19%	18 Jul →
anubis	13–5	0.03	13%	16 Jul →
vertigo	7–4	-0.03	10%	16 Jul →
train	5–5	0.13	14%	16 Jul →
inferno	12–12	0.03	26%	15 Jul →
vertigo	8–13	0.02	11%	15 Jul →
inferno	11–13	-0.00	19%	14 Jul →
mirage	9–13	-0.06	18%	14 Jul →
mirage	13–4	0.05	15%	13 Jul →
inferno	13–8	-0.01	17%	13 Jul →
anubis	9–13	0.02	15%	12 Jul →
inferno	12–12	-0.06	12%	12 Jul →
anubis	13–6	0.07	13%	12 Jul →
mirage	9–13	0.01	20%	12 Jul →
train	13–11	0.02	29%	10 Jul →
vertigo	8–13	0.00	18%	10 Jul →
inferno	9–13	0.08	19%	6 Jul →
dust2	13–6	0.08	30%	6 Jul →
anubis	13–6	0.08	38%	6 Jul →
inferno	13–10	-0.05	42%	4 Jul →
vertigo	4–13	-0.01	27%	4 Jul →
anubis	3–5	-0.09	29%	2 Jul →
inferno	4–13	0.01	19%	2 Jul →
inferno	9–13	0.01	15%	1 Jul →
mirage	11–13	-0.01	28%	30 Jun →
anubis	5–9	0.00	11%	24 Jun →
inferno	13–9	-0.01	15%	24 Jun →
train	7–13	0.00	24%	23 Jun →
anubis	13–5	0.04	25%	23 Jun →
inferno	13–8	-0.04	23%	23 Jun →
inferno	13–7	0.03	21%	21 Jun →
train	7–13	0.00	19%	21 Jun →
mirage	10–13	0.00	24%	21 Jun →
inferno	9–13	0.04	24%	18 Jun →
vertigo	13–4	0.07	17%	17 Jun →