e60.m — CS2 Stats

76561198321709655[U:1:361443927]Steam profile ↗✓ No bans

2,012Tracked matches45%Win rate2020Tracked since

CSDB Rating6.6 SolidAggressive Rifler

FaceitLevel 8Top 31.2% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim81

Positioning62

Utility55

0–100 skill scores via Leetify.

Recent form

STEADY46–47–7Last 10046%Win rateWWLLWTWLLL

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

Player DNA

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

Aim8.1

Aggression10.0

Utility5.5

Positioning6.2

Opening Duels5.4

Clutch0.0

Strong CT-side opener

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 sh1ro 91% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: 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

Strengths

CT openings. 62% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

Preaim. Mechanical aim is strong but the crosshair sits 10.3° off target when enemies appear — placement, not flicking, is the bigger win available.

T-side openings. Opening success drops from 62% on CT to 42% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 605ms 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

Aim8.1

Positioning6.2

Utility5.5

Mechanics8.1

Opening Duels5.4

Win Impact3.3

Composite 6.6/10 (Solid), 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 rating0.03+0.01

first ⅓ avg 0.01 → last ⅓ avg 0.03

Reaction time602ms−32ms

first ⅓ avg 634ms → last ⅓ avg 602ms

Headshot accuracy23.3%+5.3%

first ⅓ avg 18.0% → last ⅓ avg 23.3%

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 — nuke 13–2

13–1Biggest win — office

7Longest win streak

W2Current streak

10–3In matches decided by ≤2 rounds

4Overtime games

Map breakdown

cacheBest map · 75% over 12dust2Weakest map · 29% over 17

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	17	6–11	35%	0.03
dust2	D	17	5–12	29%	0.03
nuke	B	14	7–7	50%	0.02
cache	S	12	9–3	75%	0.02
anubis	A	10	6–4	60%	0.02
inferno	D	9	3–6	33%	0.01
ancient	D	7	2–5	29%	0.03
vertigo	C	5	2–3	40%	0.01
office	—	3	2–1	67%	0.03
train	—	2	1–1	50%	-0.01
boulder	—	2	1–1	50%	0.08
overpass	—	2	2–0	100%	0.03

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (29% over 17). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

236Matches

54%Win rate

1.34Avg K/D

80.7ADR

37%Headshot %

Clutches & streaks

0%1v1 clutch win

0%1v2 clutch win

10Longest win streak

Recent Faceit resultsWWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	2	50%	1.82	7.5
Vertigo	1	100%	1.42	17.0
Inferno	1	0%	0.67	14.0
Nuke	1	0%	1.20	24.0

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.

23.3%Headshot accuracy

38.5%Accuracy (enemy spotted)

34.9%Spray accuracy

86.5%Counter-strafing

10.3°Preaim

605msReaction time

41.7%T opening success

61.7%CT opening success

0.63Enemies flashed / flash

5.8%Flash assists

10.59HE damage / grenade

11.81Flashes / match

Recommended for you

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.

29% win rate across 17 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
nuke	10–1	0.00	31%	26 Aug →
ancient	13–10	0.07	39%	25 Aug →
mirage	5–13	-0.03	16%	25 Aug →
dust2	9–13	0.13	25%	24 Aug →
cache	13–11	0.04	21%	23 Aug →
anubis	12–12	0.00	13%	18 Aug →
mirage	13–3	0.10	33%	18 Aug →
inferno	0–5	-0.07	17%	18 Aug →
ancient	7–13	0.02	18%	17 Aug →
mirage	10–13	0.02	21%	17 Aug →
mirage	10–13	0.02	26%	17 Aug →
office	13–1	0.02	19%	15 Aug →
mirage	13–5	0.11	37%	15 Aug →
office	0–8	-0.05	33%	15 Aug →
anubis	4–13	0.06	21%	15 Aug →
nuke	5–13	-0.01	19%	13 Aug →
dust2	5–13	0.02	18%	13 Aug →
dust2	10–13	-0.00	21%	10 Aug →
mirage	13–8	0.05	26%	10 Aug →
vertigo	7–13	0.02	17%	10 Aug →
train	13–7	-0.01	11%	9 Aug →
nuke	2–13	0.03	23%	9 Aug →
inferno	9–13	0.01	17%	7 Aug →
dust2	13–4	-0.02	28%	7 Aug →
nuke	7–13	0.03	50%	6 Aug →
anubis	13–4	0.13	16%	6 Aug →
cache	13–7	0.02	29%	6 Aug →
inferno	13–7	0.03	19%	3 Aug →
cache	6–13	-0.04	23%	3 Aug →
cache	13–10	0.12	17%	29 Jul →
cache	6–13	-0.03	31%	28 Jul →
boulder	12–12	0.14	20%	28 Jul →
mirage	11–13	-0.03	14%	25 Jul →
nuke	13–7	0.03	16%	25 Jul →
nuke	3–13	0.04	22%	22 Jul →
cache	9–13	-0.02	20%	20 Jul →
dust2	12–12	0.04	22%	20 Jul →
inferno	7–9	0.03	27%	20 Jul →
cache	13–11	0.04	22%	18 Jul →
nuke	2–13	-0.08	9%	18 Jul →
cache	13–7	0.05	28%	18 Jul →
ancient	13–11	0.03	31%	18 Jul →
ancient	3–12	0.02	22%	16 Jul →
nuke	13–10	0.06	27%	16 Jul →
nuke	16–12	-0.00	26%	15 Jul →
mirage	5–13	-0.07	24%	14 Jul →
nuke	13–2	0.15	31%	13 Jul →
office	13–7	0.11	20%	13 Jul →
inferno	2–0	0.09	50%	13 Jul →
cache	13–4	0.02	32%	13 Jul →
boulder	13–11	0.01	24%	10 Jul →
mirage	5–13	-0.00	22%	9 Jul →
mirage	9–13	0.09	23%	6 Jul →
dust2	4–13	0.07	27%	5 Jul →
cache	13–8	-0.02	8%	3 Jul →
dust2	7–13	-0.03	10%	2 Jul →
dust2	13–6	0.04	13%	30 Jun →
mirage	13–8	0.03	10%	30 Jun →
cache	13–6	0.02	29%	27 Jun →
dust2	13–6	0.13	19%	27 Jun →
nuke	10–13	-0.04	23%	27 Jun →
dust2	7–13	0.04	20%	18 Jun →
mirage	13–8	0.06	23%	15 Jun →
inferno	12–12	0.02	18%	15 Jun →
overpass	13–11	0.10	26%	14 Jun →
anubis	16–14	0.03	32%	12 Jun →
dust2	5–13	-0.03	5%	12 Jun →
vertigo	4–13	0.01	20%	11 Jun →
vertigo	10–13	-0.02	14%	8 Jun →
mirage	9–13	0.05	20%	8 Jun →
dust2	8–13	0.08	25%	8 Jun →
anubis	16–13	-0.02	21%	7 Jun →
mirage	9–13	0.10	15%	7 Jun →
dust2	4–13	-0.06	9%	7 Jun →
anubis	13–10	-0.08	9%	6 Jun →
cache	13–5	0.03	22%	6 Jun →
ancient	12–12	0.03	21%	3 Jun →
vertigo	13–7	-0.05	14%	1 Jun →
anubis	12–12	0.04	19%	31 May →
mirage	5–13	-0.01	16%	30 May →
dust2	9–13	0.00	15%	30 May →
anubis	13–11	0.06	20%	30 May →
train	7–13	-0.01	18%	30 May →
dust2	11–13	0.03	19%	30 May →
inferno	9–13	-0.01	20%	29 May →
ancient	8–13	0.05	16%	28 May →
mirage	13–11	0.01	35%	25 May →
dust2	13–10	0.12	11%	25 May →
nuke	13–9	0.01	16%	24 May →
vertigo	13–6	0.07	22%	24 May →
overpass	16–14	-0.04	16%	23 May →
anubis	13–10	-0.02	24%	23 May →
dust2	13–6	0.03	15%	23 May →
mirage	10–13	0.04	24%	23 May →
nuke	7–13	0.01	14%	21 May →
inferno	4–13	-0.01	18%	21 May →
ancient	12–12	0.01	21%	19 May →
nuke	13–4	0.02	20%	18 May →
inferno	13–9	-0.02	14%	18 May →
anubis	10–13	0.04	11%	16 May →