马飞 — CS2 Stats

NE76561199076884619[U:1:1116618891]Steam profile ↗✓ No bans

1,084Tracked matches41%Win rate2022Tracked since

1,186Hours in CS

CSDB Rating4.5 Developing

FaceitLevel 9Top 20.7% of ranked FACEIT players

Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 10 among CSDB-tracked players (n=218), 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 10 median	vs Level 10
Headshot rate	50.8%	52.8%	1.9% short
Shot accuracy	9.6%	13.7%	4.1% short
Kill/death ratio	1.09	1.08	meets
Match win rate	53.7%	49.2%	above

This profile matches the typical Level 10 player on 2 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 10 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim45

Positioning46

Utility60

0–100 skill scores via Leetify.

Recent form

STEADY43–47–10Last 10043%Win rateLWWLWWLLLW

Last 10 vs previous 10: +20pp win rate · +0.05 avg rating

Player DNA

Aim4.5

Aggression6.5

Utility6.0

Positioning4.6

Opening Duels2.2

Clutch4.0

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 Twistzz 84% playstyle similarity

Most alike: opening-duel success, opening-fight frequency.

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

Areas to improve

Reaction time. 621ms 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

Aim4.5

Positioning4.6

Utility6.0

Mechanics5.7

Opening Duels2.2

Win Impact2.1

Composite 4.5/10 (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-0.00−0.02

first ⅓ avg 0.01 → last ⅓ avg -0.00

Reaction time617ms−15ms

first ⅓ avg 632ms → last ⅓ avg 617ms

Headshot accuracy16.6%−2.9%

first ⅓ avg 19.4% → 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

0.14Best rating — inferno 13–6

13–1Biggest win — anubis

8Longest win streak

9–8In matches decided by ≤2 rounds

11Overtime games

Map breakdown

mirageBest map · 59% over 17overpassWeakest map · 20% over 5

Map	Grade	Played	Record	Win rate	Avg rating
inferno	C	27	10–17	37%	0.01
ancient	C	19	7–12	37%	0.00
mirage	A	17	10–7	59%	0.00
dust2	B	13	6–7	46%	0.00
nuke	C	11	4–7	36%	-0.01
overpass	D	5	1–4	20%	-0.01
train	—	4	2–2	50%	0.02
anubis	—	2	1–1	50%	0.01
cache	—	1	1–0	100%	0.06
vertigo	—	1	1–0	100%	0.01

Across the last 100 tracked matches.

Overpass is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Overpass lineups, review the callouts, then spin up a practice server.

Lifetime stats

56,445Lifetime kills

1.09K/D · Top 50% of tracked players

3,300Matches

53.7%Match win rate · Top 10% of tracked players

50.8%Headshot % · Top 50% of tracked players

9.6%Shot accuracy

6,066MVPs

1,186Hours (in match)

2,455Bombs planted

512Bombs defused

Most-used weapons

AK-4720,440

M4A4 / M4A1-S11,870

AWP3,681

P2000 / USP-S3,514

Desert Eagle3,393

MP92,041

Glock-181,997

MAC-101,653

Galil AR1,287

FAMAS1,018

Lifetime map wins

8,536inferno

2,849dust2

2,184nuke

1,163vertigo

278train

20cbble

13italy

1ar_shoots

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

Faceit stats

Combat

130Matches

61%Win rate

1.07Avg K/D

82.5ADR

48%Headshot %

Clutches & streaks

40%1v1 clutch win

40%1v2 clutch win

9Longest win streak

Recent Faceit resultsWWWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	25	64%	1.11	15.9
Inferno	24	62%	1.34	16.4
Anubis	17	82%	1.13	15.2
Ancient	13	62%	1.19	20.7
Dust2	11	45%	0.85	15.0
Train	1	0%	1.40	21.0
Nuke	1	100%	1.17	14.0

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.

16.0%Headshot accuracy

29.4%Accuracy (enemy spotted)

29.3%Spray accuracy

75.5%Counter-strafing

10.3°Preaim

621msReaction time

37.6%T opening success

39.7%CT opening success

0.63Enemies flashed / flash

9.2%Flash assists

11.78HE damage / grenade

12.34Flashes / 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 37.5601% — below the 40% mark we flag

Spend your practice time on Overpass

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Overpass callouts & strategy →Overpass grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
inferno	7–13	-0.03	28%	6 Jul →
anubis	13–1	0.06	25%	6 Jul →
cache	13–11	0.06	26%	6 Jul →
inferno	14–16	-0.03	15%	3 Jul →
mirage	13–11	0.07	11%	3 Jul →
inferno	13–7	0.04	19%	3 Jul →
mirage	2–13	-0.08	3%	27 Jun →
dust2	7–13	-0.02	18%	27 Jun →
inferno	11–13	0.07	18%	27 Jun →
dust2	13–6	-0.03	17%	25 Jun →
dust2	13–7	-0.06	15%	25 Jun →
dust2	10–13	-0.04	15%	22 Jun →
mirage	13–5	0.01	12%	22 Jun →
mirage	6–13	-0.06	24%	22 Jun →
nuke	3–13	-0.06	6%	17 May →
inferno	5–13	-0.08	2%	17 May →
ancient	10–13	-0.02	13%	7 May →
vertigo	13–9	0.01	11%	6 May →
inferno	7–13	-0.04	8%	6 May →
inferno	5–7	-0.04	11%	6 May →
dust2	11–13	-0.03	17%	28 Feb →
inferno	11–13	0.01	20%	4 Nov →
dust2	8–13	0.00	12%	4 Nov →
mirage	13–11	0.03	18%	4 Nov →
inferno	13–7	0.01	23%	4 Nov →
inferno	7–13	-0.03	15%	3 Nov →
overpass	15–15	0.02	22%	3 Nov →
ancient	16–13	-0.02	8%	3 Nov →
train	13–3	0.05	19%	3 Nov →
nuke	3–13	0.04	22%	11 Oct →
mirage	12–12	0.04	25%	11 Oct →
dust2	4–13	0.02	25%	11 Oct →
nuke	13–10	-0.03	23%	30 Sept →
overpass	13–6	0.05	23%	3 Sept →
mirage	13–5	-0.01	32%	31 Aug →
inferno	13–10	-0.04	28%	18 Aug →
dust2	13–3	0.11	46%	18 Aug →
mirage	13–11	0.00	19%	13 Aug →
dust2	13–5	0.05	26%	13 Aug →
mirage	13–5	0.03	29%	10 Aug →
inferno	3–13	0.02	13%	10 Aug →
overpass	4–13	-0.03	30%	8 Aug →
inferno	11–13	0.01	17%	8 Aug →
ancient	13–9	-0.00	16%	8 Aug →
inferno	13–11	-0.00	27%	8 Aug →
mirage	13–7	-0.01	24%	6 Aug →
ancient	16–12	0.07	14%	2 Aug →
mirage	13–11	-0.03	14%	2 Aug →
ancient	13–16	-0.03	16%	2 Aug →
overpass	3–13	-0.05	15%	2 Aug →
nuke	5–13	-0.04	20%	2 Aug →
ancient	3–13	-0.03	20%	2 Aug →
nuke	12–12	-0.04	21%	29 Jul →
inferno	10–13	-0.02	23%	29 Jul →
dust2	16–14	-0.02	26%	24 Jul →
inferno	13–10	0.05	21%	24 Jul →
nuke	7–13	0.01	27%	24 Jul →
ancient	10–13	-0.05	13%	24 Jul →
dust2	4–13	-0.01	28%	23 Jul →
ancient	4–13	0.03	20%	23 Jul →
inferno	11–13	0.02	18%	23 Jul →
ancient	7–13	0.02	18%	22 Jul →
mirage	5–13	-0.08	29%	22 Jul →
inferno	13–11	0.01	19%	22 Jul →
inferno	7–13	0.01	24%	22 Jul →
inferno	15–15	0.00	26%	22 Jul →
nuke	12–12	0.12	21%	21 Jul →
inferno	13–5	0.07	19%	21 Jul →
mirage	5–13	0.03	28%	21 Jul →
inferno	12–12	0.07	24%	21 Jul →
ancient	13–8	0.03	33%	21 Jul →
inferno	13–10	0.05	25%	20 Jul →
nuke	13–9	0.06	24%	20 Jul →
ancient	13–11	0.01	20%	20 Jul →
nuke	13–8	-0.02	17%	18 Jul →
ancient	10–13	0.00	23%	18 Jul →
mirage	13–5	-0.04	8%	18 Jul →
overpass	2–10	-0.05	9%	17 Jul →
mirage	5–13	0.01	27%	16 Jul →
ancient	14–16	0.02	17%	14 Jul →
inferno	13–6	0.14	20%	13 Jul →
train	13–8	0.07	23%	13 Jul →
dust2	15–15	0.01	23%	13 Jul →
ancient	12–12	-0.00	23%	13 Jul →
train	10–13	-0.04	24%	12 Jul →
ancient	2–13	-0.03	10%	12 Jul →
mirage	13–6	0.06	24%	12 Jul →
ancient	13–8	0.01	21%	11 Jul →
ancient	7–13	0.05	17%	11 Jul →
inferno	8–13	-0.04	14%	10 Jul →
mirage	12–12	0.05	21%	10 Jul →
inferno	8–13	-0.03	14%	10 Jul →
nuke	0–4	-0.05	13%	9 Jul →
anubis	1–13	-0.04	17%	9 Jul →
ancient	16–13	0.01	16%	2 Jul →
nuke	13–10	-0.04	29%	2 Jul →
dust2	13–9	0.06	16%	27 Jun →
inferno	13–5	0.03	8%	27 Jun →
ancient	15–15	-0.02	14%	27 Jun →
train	10–13	0.01	23%	27 Jun →