め BTOEASy- — CS2 Stats

76561199004220857[U:1:1043955129]✓ No bans

1,206Tracked matches47%Win rate2024Tracked since

2,021Hours in CS24Hrs last 2 wks

CSDB Rating4.6 Developing

Premier CS Rating17,669Purple band · top ~17.8% of ranked players (population est.)

CSDB Leaderboard#13897 of 25988 tracked

FaceitLevel 5 · 1,172 ELOTop 67.6% of ranked FACEIT players

WingmanMaster Guardian II

Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 5 among CSDB-tracked players (n=918), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

Metric	This player	Level 5 median	Level 6 median	vs Level 6
Headshot rate	35.1%	44.2%	44.9%	9.7% short
Shot accuracy	0.0%	11.2%	11.8%	11.8% short
Kill/death ratio	1.02	1.04	1.04	0.02 short
Match win rate	46.8%	45.3%	45.3%	above

This profile matches the typical Level 6 player on 1 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 6 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim47

Positioning41

Utility65

0–100 skill scores via Leetify.

Recent form

STEADY51–49Last 10051%Win rateLWLLLWWLLW

Last 10 vs previous 10: +0pp win rate · -0.02 avg rating

Player DNA

Aim4.7

Aggression4.0

Utility6.5

Positioning4.1

Opening Duels0.8

Clutch3.8

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 82% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

Where you differ: lower positioning profile; 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

T-side openings. Opening success drops from 47% on CT to 19% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 611ms 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

Positioning4.1

Utility6.5

Mechanics5.1

Opening Duels2.1

Win Impact3.9

Composite 4.6/10 (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-0.01−0.03

first ⅓ avg 0.02 → last ⅓ avg -0.01

Reaction time610ms−5ms

first ⅓ avg 616ms → last ⅓ avg 610ms

Headshot accuracy16.6%+0.7%

first ⅓ avg 15.9% → last ⅓ avg 16.6%

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

0.19Best rating — dust2 13–6

13–0Biggest win — dust2

8Longest win streak

6–8In matches decided by ≤2 rounds

8Overtime games

Map breakdown

anubisBest map · 100% over 5infernoWeakest map · 29% over 17

Map	Grade	Played	Record	Win rate	Avg rating
dust2	A	34	20–14	59%	0.01
mirage	B	28	15–13	54%	-0.01
inferno	D	17	5–12	29%	0.03
anubis	S	5	5–0	100%	0.04
train	—	3	1–2	33%	-0.01
cache	—	3	2–1	67%	0.02
vertigo	—	3	1–2	33%	0.01
nuke	—	2	0–2	0%	-0.02
ancient	—	2	1–1	50%	0.02
overpass	—	2	1–1	50%	-0.02
office	—	1	0–1	0%	-0.02

Across the last 100 tracked matches.

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

Lifetime stats

44,835Lifetime kills

1.02K/D

3,143Matches

46.8%Match win rate · Top 50% of Level 5 players

35.1%Headshot %

0.0%Shot accuracy

5,663MVPs

1,161Hours (in match)

4,397Bombs planted

1,041Bombs defused

Most-used weapons

AK-4710,632

AWP9,138

M4A4 / M4A1-S9,094

P2000 / USP-S3,779

Glock-182,393

Desert Eagle2,084

Galil AR1,503

MP91,322

MAC-101,000

MP7887

Lifetime map wins

9,546dust2

3,864inferno

1,627nuke

1,285vertigo

641train

108office

13italy

2ar_baggage

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

178Matches

49%Win rate

1.02Avg K/D

71.9ADR

37%Headshot %

Clutches & streaks

39%1v1 clutch win

18%1v2 clutch win

6Longest win streak

Recent Faceit resultsWLLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	66	50%	1.10	13.7
Mirage	53	43%	1.00	14.7
Inferno	17	65%	0.99	13.9
Ancient	15	60%	1.07	13.4
Anubis	9	33%	0.79	10.3
Cache	9	44%	0.88	12.2
Nuke	6	50%	0.82	13.5
Overpass	2	0%	0.78	12.0

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.

16.1%Headshot accuracy

32.6%Accuracy (enemy spotted)

31.9%Spray accuracy

73.0%Counter-strafing

11.4°Preaim

611msReaction time

19.4%T opening success

47.1%CT opening success

0.61Enemies flashed / flash

4.0%Flash assists

10.85HE damage / grenade

17.42Flashes / 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.

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 19.4044% — 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.

29% win rate across 17 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
mirage	11–13	-0.01	9%	22 Aug →
dust2	13–0	-0.00	12%	22 Aug →
mirage	4–13	-0.06	23%	22 Aug →
dust2	6–13	-0.02	21%	22 Aug →
mirage	4–13	0.02	23%	22 Aug →
mirage	13–8	-0.07	11%	20 Aug →
dust2	13–6	-0.06	28%	20 Aug →
dust2	10–13	-0.00	7%	20 Aug →
mirage	10–13	-0.00	17%	18 Aug →
mirage	13–10	-0.03	17%	18 Aug →
mirage	16–14	0.01	15%	18 Aug →
dust2	4–13	-0.10	21%	17 Aug →
inferno	11–13	0.03	11%	17 Aug →
train	13–9	0.06	27%	15 Aug →
nuke	6–13	-0.03	26%	15 Aug →
dust2	4–13	0.02	19%	15 Aug →
mirage	11–13	-0.01	7%	6 Aug →
anubis	13–5	-0.05	11%	5 Aug →
inferno	8–13	0.03	24%	5 Aug →
mirage	13–8	0.02	8%	3 Aug →
dust2	13–11	-0.06	10%	2 Aug →
dust2	13–10	-0.05	12%	2 Aug →
inferno	5–13	-0.02	26%	1 Aug →
dust2	13–7	-0.01	23%	1 Aug →
dust2	12–16	-0.04	14%	31 Jul →
mirage	13–6	0.03	15%	31 Jul →
inferno	8–13	0.00	17%	27 Jul →
mirage	13–11	0.03	10%	26 Jul →
anubis	13–3	0.08	18%	23 Jul →
inferno	7–9	-0.01	13%	23 Jul →
dust2	9–13	-0.08	13%	21 Jul →
mirage	4–13	-0.06	23%	20 Jul →
mirage	13–2	0.04	18%	20 Jul →
dust2	13–6	0.07	13%	19 Jul →
ancient	1–13	-0.07	7%	16 Jul →
mirage	13–5	-0.06	13%	16 Jul →
dust2	3–13	-0.00	9%	15 Jul →
mirage	13–5	0.03	20%	14 Jul →
mirage	6–13	-0.02	26%	14 Jul →
inferno	8–13	0.05	30%	13 Jul →
mirage	7–13	-0.03	17%	13 Jul →
mirage	0–7	-0.06	27%	13 Jul →
dust2	8–13	0.04	18%	13 Jul →
dust2	13–7	0.12	18%	13 Jul →
dust2	13–1	0.11	30%	13 Jul →
inferno	11–13	0.07	18%	12 Jul →
inferno	13–11	0.12	25%	11 Jul →
mirage	13–7	0.09	32%	11 Jul →
dust2	16–12	0.06	35%	11 Jul →
dust2	13–9	-0.03	15%	11 Jul →
nuke	5–13	-0.01	8%	11 Jul →
mirage	16–14	-0.01	22%	10 Jul →
dust2	13–8	0.02	14%	10 Jul →
mirage	5–13	-0.01	7%	10 Jul →
cache	10–13	0.01	19%	9 Jul →
dust2	16–12	-0.01	15%	9 Jul →
office	8–13	-0.02	20%	8 Jul →
dust2	13–8	0.01	20%	7 Jul →
inferno	9–4	0.03	27%	7 Jul →
dust2	10–13	-0.08	10%	6 Jul →
inferno	10–13	0.01	8%	6 Jul →
dust2	2–13	-0.06	14%	6 Jul →
inferno	5–13	0.10	9%	4 Jul →
vertigo	2–9	-0.11	13%	4 Jul →
anubis	13–4	0.07	26%	4 Jul →
dust2	13–5	0.10	31%	4 Jul →
inferno	5–9	-0.01	28%	3 Jul →
cache	13–9	0.02	17%	1 Jul →
cache	13–6	0.04	12%	1 Jul →
mirage	16–13	0.00	9%	1 Jul →
dust2	13–6	0.19	30%	28 Jun →
mirage	13–10	0.02	33%	28 Jun →
inferno	13–10	0.06	28%	28 Jun →
anubis	13–5	0.08	23%	28 Jun →
ancient	13–8	0.10	24%	28 Jun →
mirage	11–13	-0.10	16%	20 Jun →
mirage	13–9	0.00	14%	20 Jun →
dust2	13–10	-0.04	7%	20 Jun →
dust2	13–3	0.04	12%	19 Jun →
inferno	9–13	0.09	22%	17 Jun →
train	10–13	-0.08	16%	17 Jun →
train	1–13	-0.01	3%	17 Jun →
mirage	13–6	0.02	4%	14 Jun →
mirage	3–13	-0.08	13%	14 Jun →
dust2	13–6	0.06	17%	13 Jun →
overpass	10–13	-0.08	10%	12 Jun →
dust2	16–14	0.03	14%	11 Jun →
overpass	13–5	0.04	10%	10 Jun →
dust2	10–13	0.02	18%	9 Jun →
dust2	11–13	0.02	16%	6 Jun →
vertigo	13–1	0.16	15%	3 Jun →
vertigo	9–13	-0.03	20%	3 Jun →
inferno	9–13	0.03	13%	1 Jun →
dust2	13–6	-0.03	16%	1 Jun →
mirage	14–16	0.02	15%	31 May →
dust2	9–13	0.07	17%	31 May →
anubis	13–6	0.00	20%	29 May →
inferno	9–5	-0.02	23%	29 May →
inferno	9–6	0.03	14%	29 May →
dust2	5–13	-0.04	6%	27 May →