my balls large — CS2 Stats

76561198213632420[U:1:253366692]✓ No bans

895Tracked matches52%Win rate2020Tracked since

CSDB Rating7.9 StrongEntry Fragger

Premier CS Rating22,817Top 50% of 819 CSDB-tracked playersPink band · top ~5.4% of ranked players (population est.)

FaceitLevel 10Top 12.4% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim96

Positioning79

Utility51

0–100 skill scores via Leetify.

Recent form

STEADY54–39–7Last 10054%Win rateWLLWLWLLWL

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

Player DNA

Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.

Aim9.6

Aggression10.0

Utility5.1

Positioning7.9

Opening Duels7.3

Sharp aimerStrong CT-side openerEffective flashes

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 s1mple 96% playstyle similarity

Most alike: opening-fight frequency, positioning 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

Aim. Aim score of 96 — the mechanical foundation is a clear strength.

CT openings. 73% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Flashes. 0.98 enemies blinded per flash — utility that consistently lands.

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 73% on CT to 45% 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

Aim9.6

Positioning7.9

Utility5.1

Mechanics8.3

Opening Duels6.9

Win Impact5.6

Composite 7.9/10 (Strong), 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 rating0.04+0.04

first ⅓ avg 0.01 → last ⅓ avg 0.04

Reaction time519ms−27ms

first ⅓ avg 545ms → last ⅓ avg 519ms

Headshot accuracy26.6%−7.1%

first ⅓ avg 33.7% → last ⅓ avg 26.6%

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 — dust2 13–7

13–0Biggest win — nuke

7Longest win streak

7–9In matches decided by ≤2 rounds

13Overtime games

Map breakdown

nukeBest map · 78% over 9infernoWeakest map · 42% over 12

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	33	16–17	48%	0.03
mirage	S	30	21–9	70%	0.04
inferno	C	12	5–7	42%	0.04
nuke	S	9	7–2	78%	0.03
overpass	A	5	3–2	60%	0.04
cache	—	3	1–2	33%	-0.02
anubis	—	3	0–3	0%	-0.02
train	—	2	0–2	0%	-0.02
vertigo	—	1	0–1	0%	0.05
ancient	—	1	1–0	100%	-0.03
office	—	1	0–1	0%	-0.12

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (42% over 12). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

351Matches

59%Win rate

1.29Avg K/D

—ADR

46%Headshot %

Clutches & streaks

—1v1 clutch win

—1v2 clutch win

10Longest win streak

Recent Faceit resultsLLWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	2	0%	0.80	13.0
Vertigo	2	50%	1.14	18.5
Nuke	1	100%	1.55	17.0

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.

26.1%Headshot accuracy

40.6%Accuracy (enemy spotted)

42.3%Spray accuracy

87.4%Counter-strafing

6.3°Preaim

517msReaction time

44.8%T opening success

73.3%CT opening success

0.98Enemies flashed / flash

5.7%Flash assists

9.53HE damage / grenade

10.17Flashes / match

Recommended for you

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.

42% win rate across 12 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
dust2	13–7	0.09	21%	28 Aug →
mirage	7–13	0.13	29%	25 Aug →
dust2	6–13	0.00	18%	24 Aug →
mirage	13–10	0.01	27%	24 Aug →
dust2	10–13	-0.03	43%	24 Aug →
nuke	13–10	0.06	26%	24 Aug →
dust2	4–13	-0.02	43%	24 Aug →
mirage	9–13	-0.01	22%	23 Aug →
dust2	13–10	0.12	24%	23 Aug →
inferno	1–13	-0.01	29%	23 Aug →
dust2	15–15	0.08	38%	23 Aug →
mirage	13–2	0.03	28%	22 Aug →
dust2	16–12	0.07	26%	22 Aug →
mirage	13–4	0.09	15%	22 Aug →
dust2	9–13	0.06	32%	20 Aug →
cache	13–10	0.00	18%	20 Aug →
nuke	13–11	0.02	21%	20 Aug →
dust2	15–15	0.09	24%	20 Aug →
mirage	13–10	0.02	19%	20 Aug →
inferno	10–13	0.11	27%	19 Aug →
dust2	13–6	0.12	31%	19 Aug →
inferno	11–13	0.05	26%	18 Aug →
dust2	13–9	0.09	20%	18 Aug →
mirage	13–5	0.03	27%	9 Aug →
dust2	11–13	0.03	44%	9 Aug →
train	3–13	-0.01	30%	9 Aug →
vertigo	12–12	0.05	15%	9 Aug →
cache	2–13	-0.05	20%	26 Jul →
mirage	16–13	0.03	17%	25 Jul →
dust2	7–13	0.02	25%	25 Jul →
dust2	13–5	0.05	42%	25 Jul →
mirage	4–13	0.02	31%	25 Jul →
inferno	16–12	0.10	22%	25 Jul →
nuke	13–7	0.03	19%	24 Jul →
dust2	11–13	-0.03	42%	21 Jul →
dust2	10–13	-0.03	38%	21 Jul →
mirage	5–13	0.05	17%	11 Jul →
cache	6–13	-0.00	22%	11 Jul →
dust2	13–3	-0.01	39%	10 Jul →
mirage	5–13	0.01	26%	10 Jul →
nuke	16–13	0.08	30%	2 Jul →
dust2	13–3	0.10	28%	2 Jul →
mirage	4–13	0.01	25%	1 Jul →
mirage	13–8	0.07	19%	1 Jul →
dust2	10–13	0.03	26%	1 Jul →
inferno	10–13	0.12	30%	1 Jul →
mirage	13–4	0.12	32%	1 Jul →
dust2	13–4	-0.07	35%	29 Jun →
mirage	11–13	0.04	26%	29 Jun →
overpass	14–16	0.04	19%	29 Jun →
mirage	13–9	-0.01	23%	28 Jun →
dust2	13–11	0.05	23%	28 Jun →
mirage	13–10	-0.06	37%	28 Jun →
nuke	16–13	0.11	43%	22 Jun →
dust2	13–7	0.14	21%	22 Jun →
nuke	13–0	-0.01	0%	21 Jun →
mirage	13–8	0.07	24%	21 Jun →
anubis	5–13	-0.05	33%	21 Jun →
mirage	13–11	0.05	25%	21 Jun →
inferno	13–5	0.05	28%	21 Jun →
nuke	13–2	0.03	27%	21 Jun →
dust2	16–13	-0.03	35%	21 Jun →
inferno	15–15	0.09	25%	20 Jun →
mirage	16–13	0.03	22%	18 Jun →
dust2	13–11	0.08	48%	18 Jun →
ancient	13–4	-0.03	17%	17 Jun →
dust2	13–6	0.10	52%	17 Jun →
anubis	13–16	-0.02	25%	16 Jun →
overpass	13–10	0.02	43%	15 Jun →
dust2	13–9	0.01	37%	15 Jun →
overpass	13–8	0.04	24%	23 May →
inferno	13–8	0.02	26%	4 Apr →
mirage	13–6	0.08	36%	4 Apr →
overpass	13–10	0.06	41%	4 Apr →
nuke	7–13	0.00	42%	4 Apr →
dust2	11–13	-0.02	43%	4 Apr →
mirage	16–14	0.03	27%	4 Apr →
anubis	8–13	0.00	28%	24 Mar →
dust2	4–9	-0.01	13%	21 Mar →
mirage	13–5	0.05	27%	21 Mar →
inferno	5–13	-0.01	36%	2 Feb →
inferno	13–11	-0.03	19%	31 Jan →
mirage	13–6	0.03	28%	31 Jan →
mirage	7–2	-0.00	63%	11 Jan →
train	2–8	-0.03	21%	28 Nov →
mirage	11–13	-0.01	42%	28 Nov →
dust2	4–13	-0.05	21%	28 Nov →
inferno	12–12	-0.09	39%	28 Nov →
mirage	12–12	0.03	16%	28 Nov →
nuke	3–7	-0.06	40%	27 Nov →
mirage	13–11	0.04	22%	25 Nov →
dust2	6–13	0.03	20%	25 Nov →
overpass	11–13	0.04	29%	23 Nov →
dust2	13–2	0.01	43%	23 Nov →
inferno	10–5	0.06	68%	23 Nov →
mirage	13–7	0.06	50%	23 Nov →
office	0–5	-0.12	0%	16 Nov →
mirage	13–1	0.06	39%	16 Nov →
dust2	12–12	0.00	43%	16 Nov →
dust2	11–13	-0.03	60%	15 Nov →