Szabo☺ — CS2 Stats

76561199499137776[U:1:1538872048]Steam profile ↗✓ No bans

1,514Tracked matches50%Win rate2023Tracked since

762Hours in CS

CSDB Rating4.2 Developing

Premier CS Rating14,718Blue band · top ~29.9% of ranked players (population est.)

CSDB Leaderboard#35251 of 57470 tracked

FaceitLevel 8 · 1,676 ELOTop 31.2% of ranked FACEIT players

Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 8 among CSDB-tracked players (n=3,003), 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 8 median	Level 9 median	vs Level 9
Headshot rate	53.0%	47.0%	48.4%	above
Shot accuracy	0.5%	12.8%	13.2%	12.7% short
Kill/death ratio	1.20	1.07	1.08	above
Match win rate	47.8%	46.4%	47.0%	meets

This profile matches the typical Level 9 player on 3 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 9 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim42

Positioning53

Utility41

0–100 skill scores via Leetify.

Recent form

STEADY40–52–8Last 10040%Win rateWWWWWLLLLL

Last 10 vs previous 10: +10pp win rate · +0.00 avg rating

Player DNA

Aim4.2

Aggression6.4

Utility4.1

Positioning5.3

Opening Duels3.1

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 ropz 82% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

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. 613ms 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

Aim4.2

Positioning5.3

Utility4.1

Mechanics4.5

Opening Duels3.1

Win Impact5.0

Composite 4.2/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.00+0.00

first ⅓ avg -0.00 → last ⅓ avg -0.00

Reaction time620ms+39ms

first ⅓ avg 581ms → last ⅓ avg 620ms

Headshot accuracy13.2%+0.1%

first ⅓ avg 13.1% → last ⅓ avg 13.2%

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

0.09Best rating — mirage 11–13

13–2Biggest win — dust2

5Longest win streak

W5Current streak

5–12In matches decided by ≤2 rounds

3Overtime games

Map breakdown

mirageBest map · 58% over 12trainWeakest map · 0% over 5

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	25	9–16	36%	-0.01
cache	D	16	5–11	31%	-0.01
ancient	B	15	7–8	47%	-0.00
mirage	A	12	7–5	58%	-0.00
nuke	D	12	4–8	33%	0.02
anubis	A	7	4–3	57%	0.02
train	D	5	0–5	0%	0.01
inferno	—	2	1–1	50%	0.04
office	—	2	1–1	50%	0.02
overpass	—	2	0–2	0%	-0.03
boulder	—	1	1–0	100%	-0.06
vertigo	—	1	1–0	100%	-0.04

Across the last 100 tracked matches.

Lifetime stats

35,625Lifetime kills

1.20K/D · Top 50% of Level 8 players

1,553Matches

47.8%Match win rate · Top 50% of Level 8 players

53.0%Headshot % · Top 25% of Level 8 players

0.5%Shot accuracy

3,613MVPs

762Hours (in match)

1,591Bombs planted

795Bombs defused

Most-used weapons

AK-4720,640

M4A4 / M4A1-S5,441

MP91,235

P2000 / USP-S981

AWP899

MAC-10810

Galil AR711

Desert Eagle702

FAMAS676

Glock-18588

Lifetime map wins

2,644dust2

1,462inferno

1,434nuke

1,113train

1,082vertigo

287office

39lake

22italy

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

Faceit stats

Combat

433Matches

53%Win rate

1.03Avg K/D

73.2ADR

39%Headshot %

Clutches & streaks

40%1v1 clutch win

24%1v2 clutch win

10Longest win streak

Recent Faceit resultsWWWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	104	55%	1.01	14.0
Anubis	80	64%	1.09	14.6
Ancient	65	43%	0.96	14.5
Inferno	45	49%	0.92	12.8
Dust2	40	62%	1.08	14.9
Vertigo	38	42%	1.13	15.2
Nuke	22	36%	1.03	13.8
Overpass	22	50%	1.00	14.1

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.

12.9%Headshot accuracy

33.4%Accuracy (enemy spotted)

35.7%Spray accuracy

70.1%Counter-strafing

12.2°Preaim

613msReaction time

35.3%T opening success

49.3%CT opening success

0.57Enemies flashed / flash

10.3%Flash assists

2.84HE damage / grenade

10.08Flashes / 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
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 12.2346° — above the 12° mark we flag
Aim Training →
Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 12.8962% — below the 15% mark we flag
Aim Training →

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.

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