andy — CS2 Stats

76561198027103392[U:1:66837664]

682Tracked matches66%Win rate2020Tracked since

CSDB Rating8.1 StrongAggressive Rifler

Premier CS Rating26,138Top 10% of 29,473 CSDB-tracked playersRed band · top ~2.5% of ranked players (population est.)

CSDB Leaderboard#3897 of 53649 tracked

FaceitLevel 10 · 2,231 ELOTop 12.4% of ranked FACEIT players

WingmanSupreme Master First Class

Ladder ranks via Leetify

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Performance scores

Aim88

Positioning71

Utility54

0–100 skill scores via Leetify.

Recent form

HOT55–44–1Last 10055%Win rateWWTLWWWWLW

Last 10 vs previous 10: +20pp win rate · +0.02 avg rating

Player DNA

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

Aim8.8

Aggression10.0

Utility5.4

Positioning7.1

Opening Duels5.1

Clutch4.2

Sharp aimerExcellent counter-strafingStrong 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 ZywOo 93% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

Where you differ: lower utility contribution.

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

Aim. Aim score of 88 — the mechanical foundation is a clear strength.

Areas to improve

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

T-side openings. Opening success drops from 60% on CT to 42% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim8.8

Positioning7.1

Utility5.4

Mechanics8.6

Opening Duels5.1

Win Impact10.0

Composite 8.1/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02+0.01

first ⅓ avg 0.01 → last ⅓ avg 0.02

Reaction time553ms−35ms

first ⅓ avg 588ms → last ⅓ avg 553ms

Headshot accuracy24.5%+0.3%

first ⅓ avg 24.2% → last ⅓ avg 24.5%

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 13–8

13–2Biggest win — dust2

4Longest win streak

W2Current streak

11–10In matches decided by ≤2 rounds

13Overtime games

Map breakdown

anubisBest map · 80% over 5trainWeakest map · 20% over 5

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	21	11–10	52%	0.02
dust2	A	21	13–8	62%	0.02
inferno	C	13	5–8	38%	0.03
ancient	A	12	7–5	58%	0.02
nuke	A	11	6–5	55%	0.04
cache	A	8	5–3	63%	0.04
anubis	S	5	4–1	80%	0.04
train	D	5	1–4	20%	0.00
overpass	—	3	2–1	67%	-0.02
grail	—	1	1–0	100%	0.00

Across the last 100 tracked matches.

Faceit stats

Combat

802Matches

52%Win rate

1.23Avg K/D

83.7ADR

59%Headshot %

Clutches & streaks

41%1v1 clutch win

25%1v2 clutch win

9Longest win streak

Recent Faceit resultsWWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	119	48%	1.15	18.2
Dust2	104	59%	1.09	16.1
Ancient	71	42%	1.07	16.3
Nuke	53	51%	1.30	17.8
Inferno	34	50%	1.17	16.8
Anubis	30	50%	1.15	16.4
Train	25	48%	1.24	18.8
Vertigo	16	44%	1.13	16.5

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.

23.1%Headshot accuracy

36.2%Accuracy (enemy spotted)

44.0%Spray accuracy

88.9%Counter-strafing

9.8°Preaim

549msReaction time

41.5%T opening success

59.7%CT opening success

0.48Enemies flashed / flash

10.4%Flash assists

9.63HE damage / grenade

8.26Flashes / 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 0.4756 — below the 0.5 mark we flag
Grenade Lineups →

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.

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

Train callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
cache	13–7	0.07	21%	30 Aug →
mirage	13–11	0.06	30%	30 Aug →
ancient	15–15	0.02	16%	25 Aug →
cache	10–13	0.03	17%	25 Aug →
nuke	13–11	0.04	30%	24 Aug →
cache	13–10	0.02	13%	24 Aug →
ancient	13–7	0.02	28%	24 Aug →
dust2	13–10	0.00	23%	24 Aug →
inferno	9–13	0.07	16%	24 Aug →
cache	13–5	0.01	33%	23 Aug →
dust2	10–13	-0.01	20%	23 Aug →
ancient	13–3	0.01	19%	23 Aug →
cache	11–13	0.01	25%	23 Aug →
anubis	13–4	0.01	15%	23 Aug →
nuke	16–13	0.09	25%	23 Aug →
inferno	5–13	0.03	26%	23 Aug →
dust2	13–10	0.01	31%	23 Aug →
cache	6–13	-0.02	22%	23 Aug →
dust2	11–13	-0.06	18%	16 Aug →
inferno	13–7	0.08	21%	16 Aug →
mirage	13–7	0.03	32%	16 Aug →
cache	13–10	0.07	27%	16 Aug →
dust2	11–13	-0.00	37%	16 Aug →
anubis	13–11	0.04	30%	22 Jul →
cache	13–4	0.11	24%	22 Jul →
dust2	9–13	0.02	14%	22 Jul →
dust2	13–9	0.02	15%	22 Jul →
nuke	16–14	-0.02	18%	27 Jun →
inferno	13–10	-0.01	17%	27 Jun →
nuke	14–16	0.06	30%	26 Jun →
mirage	13–11	-0.04	35%	3 Jun →
nuke	11–13	0.04	58%	3 Jun →
mirage	9–13	-0.04	24%	19 May →
mirage	16–14	-0.00	29%	12 May →
ancient	13–3	0.06	30%	23 Apr →
nuke	13–16	0.03	23%	12 Jan →
nuke	16–14	0.07	32%	12 Jan →
mirage	13–7	0.04	31%	12 Nov →
ancient	6–13	-0.05	23%	24 Oct →
mirage	7–13	0.05	14%	22 Oct →
dust2	11–13	0.00	33%	17 Oct →
dust2	3–13	0.01	21%	16 Oct →
mirage	13–9	0.05	29%	16 Oct →
ancient	13–10	0.06	21%	16 Oct →
dust2	13–5	0.08	27%	15 Oct →
ancient	6–13	0.03	32%	15 Oct →
inferno	9–4	0.14	11%	10 Oct →
dust2	13–8	0.12	26%	8 Oct →
mirage	13–9	-0.03	23%	29 Sept →
ancient	7–13	-0.00	22%	22 Sept →
mirage	5–13	0.07	33%	22 Sept →
dust2	13–8	-0.00	25%	22 Sept →
mirage	9–13	0.06	23%	16 Sept →
ancient	13–6	0.02	18%	12 Sept →
mirage	16–13	0.02	21%	9 Sept →
ancient	11–13	0.01	20%	2 Sept →
ancient	13–7	0.03	16%	1 Sept →
mirage	16–13	0.01	25%	1 Sept →
dust2	13–2	0.04	21%	28 Aug →
overpass	13–10	0.03	18%	27 Aug →
inferno	9–13	0.08	25%	26 Aug →
train	11–13	-0.02	9%	26 Aug →
mirage	10–13	0.01	37%	22 Aug →
ancient	13–3	0.07	22%	20 Aug →
inferno	3–13	-0.01	17%	18 Aug →
dust2	13–7	0.06	10%	18 Aug →
train	13–16	-0.04	25%	13 Aug →
mirage	19–17	0.04	27%	12 Aug →
dust2	10–13	0.03	26%	6 Aug →
train	13–11	0.06	18%	6 Aug →
dust2	13–7	0.02	26%	5 Aug →
nuke	6–13	-0.05	17%	5 Aug →
nuke	13–16	0.01	28%	1 Aug →
mirage	13–6	0.02	29%	1 Aug →
dust2	6–13	0.02	33%	24 Jul →
train	6–13	-0.01	26%	23 Jul →
overpass	5–13	-0.06	24%	23 Jul →
mirage	9–13	-0.00	23%	18 Jul →
overpass	13–8	-0.02	29%	18 Jul →
inferno	9–13	-0.03	24%	15 Jul →
mirage	6–13	0.01	8%	15 Jul →
mirage	5–13	-0.02	10%	14 Jul →
inferno	3–13	-0.06	17%	11 Jul →
mirage	10–13	0.03	22%	11 Jul →
inferno	7–13	0.01	27%	9 Jul →
inferno	13–3	0.02	24%	9 Jul →
anubis	13–11	0.07	21%	9 Jul →
anubis	7–13	-0.02	21%	8 Jul →
dust2	11–3	-0.02	25%	2 Jul →
mirage	11–13	-0.03	22%	2 Jul →
dust2	13–10	0.01	36%	20 Jun →
dust2	16–13	0.01	24%	20 Jun →
dust2	13–3	-0.01	28%	11 Jun →
nuke	13–8	0.15	29%	8 Jun →
train	11–13	0.03	30%	8 Jun →
inferno	4–13	-0.04	26%	6 Jun →
grail	13–6	0.00	23%	6 Jun →
anubis	13–5	0.10	25%	6 Jun →
nuke	13–11	0.02	32%	4 Jun →
inferno	13–9	0.09	20%	25 May →