Master Folk — CS2 Stats

76561198418987517[U:1:458721789]

801Tracked matches62%Win rate2020Tracked since

1,919Hours in CS10Hrs last 2 wks

CSDB Rating6.9 SolidAggressive Rifler

Premier CS Rating20,729Pink band · top ~7.7% of ranked players (population est.)

CSDB Leaderboard#4092 of 9846 tracked

FaceitLevel 4Top 81.0% of ranked FACEIT players

WingmanMaster Guardian Elite

Ladder ranks via Leetify

Share this profile

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim86

Positioning56

Utility29

0–100 skill scores via Leetify.

Recent form

COLD52–40–8Last 10052%Win rateLWWLLLLTWL

Last 10 vs previous 10: -30pp win rate · -0.04 avg rating

Player DNA

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

Aim8.6

Aggression8.6

Utility2.9

Positioning5.6

Opening Duels3.8

Clutch7.2

Sharp aimerExcellent counter-strafingReliable in 1v1s

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 88% playstyle similarity

Most alike: positioning profile, opening-duel success.

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 86 — the mechanical foundation is a clear strength.

Counter-strafing. 92% of shots taken properly stopped — movement discipline most players never reach.

Areas to improve

Positioning. Positioning trails aim by 30 points — deaths here waste a strong aim profile.

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

Reaction time. 584ms 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

Aim8.6

Positioning5.6

Utility2.9

Mechanics9.4

Opening Duels3.8

Win Impact8.8

Composite 6.9/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01−0.01

first ⅓ avg 0.02 → last ⅓ avg 0.01

Reaction time584ms−12ms

first ⅓ avg 596ms → last ⅓ avg 584ms

Headshot accuracy18.9%−1.0%

first ⅓ avg 19.9% → last ⅓ avg 18.9%

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

0.18Best rating — dust2 13–3

13–0Biggest win — train

5Longest win streak

4–10In matches decided by ≤2 rounds

7Overtime games

Map breakdown

cacheBest map · 62% over 13anubisWeakest map · 14% over 7

Map	Grade	Played	Record	Win rate	Avg rating
nuke	A	29	16–13	55%	0.03
dust2	C	14	6–8	43%	0.02
cache	A	13	8–5	62%	0.00
mirage	A	11	6–5	55%	-0.00
inferno	A	9	5–4	56%	0.02
anubis	D	7	1–6	14%	-0.02
ancient	A	7	4–3	57%	-0.01
train	A	5	3–2	60%	0.07
overpass	—	2	1–1	50%	0.06
vertigo	—	2	2–0	100%	0.09
debris	—	1	0–1	0%	0.00

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (14% over 7). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

52,437Lifetime kills

1.04K/D

3,420Matches

42.4%Match win rate

40.2%Headshot %

9.6%Shot accuracy

5,467MVPs

1,196Hours (in match)

1,106Bombs planted

313Bombs defused

Most-used weapons

AK-4718,083

M4A4 / M4A1-S11,178

AWP8,462

Desert Eagle2,733

P2000 / USP-S2,358

SSG 081,562

Glock-181,137

AUG1,125

Galil AR786

SG 553783

Lifetime map wins

8,571nuke

1,913inferno

1,899dust2

1,145vertigo

738office

664train

195italy

111cbble

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

Faceit stats

Combat

33Matches

48%Win rate

0.95Avg K/D

84.7ADR

46%Headshot %

Clutches & streaks

56%1v1 clutch win

15%1v2 clutch win

5Longest win streak

Recent Faceit resultsLWLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	11	64%	1.00	16.6
Inferno	7	57%	0.79	14.1
Dust2	5	20%	1.02	22.6
Anubis	5	60%	1.03	16.4
Ancient	3	33%	0.97	18.7
Nuke	2	0%	0.81	22.0

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.

18.8%Headshot accuracy

37.1%Accuracy (enemy spotted)

38.3%Spray accuracy

92.1%Counter-strafing

7.7°Preaim

584msReaction time

48.1%T opening success

42.4%CT opening success

0.43Enemies flashed / flash

3.3%Flash assists

5.77HE damage / grenade

6.88Flashes / 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 0.4252 — below the 0.5 mark we flag
Grenade Lineups →

Spend your practice time on Anubis

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

14% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
anubis	7–13	-0.04	20%	21 Aug →
cache	13–5	-0.04	13%	21 Aug →
nuke	13–3	0.09	19%	21 Aug →
ancient	2–13	-0.02	30%	20 Aug →
anubis	13–16	-0.05	17%	20 Aug →
dust2	9–13	0.01	21%	20 Aug →
ancient	8–13	-0.04	10%	20 Aug →
nuke	15–15	-0.03	9%	16 Aug →
nuke	13–10	-0.04	10%	15 Aug →
inferno	4–13	-0.09	39%	15 Aug →
dust2	12–12	-0.03	19%	15 Aug →
dust2	13–11	0.04	17%	14 Aug →
nuke	13–4	-0.05	15%	13 Aug →
cache	13–8	-0.02	18%	13 Aug →
train	13–7	0.10	31%	13 Aug →
nuke	8–8	0.06	9%	13 Aug →
debris	5–9	0.00	21%	13 Aug →
dust2	12–12	0.01	16%	12 Aug →
inferno	16–12	0.05	18%	12 Aug →
mirage	16–13	0.00	25%	11 Aug →
dust2	13–3	0.18	13%	11 Aug →
dust2	2–13	0.01	18%	11 Aug →
nuke	13–6	0.08	19%	11 Aug →
mirage	13–4	0.06	17%	11 Aug →
nuke	9–13	0.01	25%	11 Aug →
anubis	11–13	-0.05	15%	10 Aug →
ancient	13–10	-0.01	21%	10 Aug →
train	12–12	-0.02	26%	10 Aug →
nuke	11–13	0.01	14%	9 Aug →
nuke	13–8	0.04	14%	9 Aug →
nuke	13–11	0.01	21%	8 Aug →
nuke	13–5	0.13	24%	8 Aug →
nuke	13–3	0.06	21%	8 Aug →
mirage	9–13	-0.10	16%	8 Aug →
nuke	13–7	0.09	19%	8 Aug →
mirage	6–13	0.01	10%	8 Aug →
mirage	15–15	0.08	20%	8 Aug →
inferno	13–4	0.05	36%	8 Aug →
cache	13–7	0.04	20%	7 Aug →
mirage	13–4	0.02	16%	7 Aug →
inferno	13–6	0.11	20%	7 Aug →
anubis	8–13	-0.05	22%	6 Aug →
nuke	11–13	0.12	18%	6 Aug →
dust2	13–1	0.00	18%	6 Aug →
nuke	7–13	-0.01	16%	5 Aug →
ancient	13–10	-0.02	13%	5 Aug →
inferno	11–13	0.05	23%	5 Aug →
nuke	13–10	-0.02	24%	5 Aug →
cache	13–10	-0.04	20%	4 Aug →
inferno	13–16	0.06	16%	4 Aug →
cache	13–9	-0.02	7%	4 Aug →
nuke	13–7	0.06	14%	4 Aug →
dust2	4–1	-0.05	17%	3 Aug →
mirage	9–13	-0.02	8%	3 Aug →
cache	10–13	0.08	21%	3 Aug →
cache	10–0	-0.01	27%	3 Aug →
inferno	13–10	-0.01	22%	3 Aug →
nuke	13–10	-0.01	22%	2 Aug →
cache	11–13	-0.02	12%	1 Aug →
anubis	6–13	-0.09	10%	1 Aug →
nuke	11–13	0.08	16%	31 Jul →
cache	13–11	0.01	23%	31 Jul →
overpass	13–6	0.11	18%	31 Jul →
ancient	13–5	0.00	18%	31 Jul →
dust2	13–8	-0.00	26%	30 Jul →
mirage	13–10	-0.04	16%	30 Jul →
overpass	8–13	0.01	17%	30 Jul →
inferno	12–1	-0.02	17%	30 Jul →
vertigo	13–1	0.10	15%	30 Jul →
nuke	13–7	-0.01	38%	28 Jul →
train	13–9	0.12	16%	28 Jul →
nuke	9–13	0.06	15%	28 Jul →
train	13–0	0.14	0%	28 Jul →
anubis	13–6	0.03	24%	28 Jul →
cache	10–13	0.01	18%	28 Jul →
inferno	10–13	-0.01	21%	28 Jul →
dust2	11–13	0.00	28%	28 Jul →
ancient	12–12	0.04	21%	27 Jul →
cache	12–12	-0.02	22%	27 Jul →
dust2	8–13	-0.00	12%	27 Jul →
cache	9–13	0.01	21%	27 Jul →
nuke	6–13	-0.02	20%	27 Jul →
nuke	13–4	0.01	23%	26 Jul →
anubis	10–13	0.11	16%	25 Jul →
nuke	13–6	0.05	13%	25 Jul →
dust2	13–16	0.02	22%	25 Jul →
dust2	13–10	0.01	12%	24 Jul →
mirage	13–11	0.01	8%	22 Jul →
nuke	11–13	-0.03	22%	22 Jul →
nuke	11–13	0.04	30%	21 Jul →
cache	7–1	0.06	17%	21 Jul →
ancient	13–10	0.00	23%	20 Jul →
vertigo	13–10	0.07	18%	19 Jul →
mirage	11–13	-0.06	23%	19 Jul →
nuke	7–13	-0.00	28%	19 Jul →
nuke	13–6	0.00	27%	18 Jul →
mirage	13–9	0.04	26%	18 Jul →
nuke	5–13	-0.03	19%	17 Jul →
train	5–13	0.01	15%	17 Jul →
dust2	9–13	0.05	28%	16 Jul →