sl3nd — CS2 Stats

PROINFINITE ESPORTSHungaryAWPerSettings & gear profile →

HU76561198098071693[U:1:137805965]Steam profile ↗✓ No bans

4,788Tracked matches50%Win rate2020Tracked since

CSDB Rating8.3 StrongEntry Fragger

Premier CS Rating25,711Top 25% of 819 CSDB-tracked playersRed band · top ~2.7% of ranked players (population est.)

CSDB Leaderboard#1577 of 12716 tracked

FaceitLevel 10 · 4,539 ELOTop 12.4% of ranked FACEIT players

WingmanThe Global Elite

Ladder ranks via Leetify

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Performance scores

Aim96

Positioning74

Utility74

0–100 skill scores via Leetify.

Recent form

COLD63–37Last 10063%Win rateWLWLLWLLLL

Last 10 vs previous 10: -40pp win rate · +0.01 avg rating

Player DNA

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

Aim9.6

Aggression10.0

Utility7.4

Positioning7.4

Opening Duels6.6

Clutch4.4

Sharp aimerExcellent counter-strafingStrong 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, 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

Strengths

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

CT openings. 68% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

T-side openings. Opening success drops from 68% on CT to 44% 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

Positioning7.4

Utility7.4

Mechanics8.7

Opening Duels6.6

Win Impact5.0

Composite 8.3/10 (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 rating0.04+0.00

first ⅓ avg 0.04 → last ⅓ avg 0.04

Reaction time424ms−9ms

first ⅓ avg 434ms → last ⅓ avg 424ms

Headshot accuracy21.1%+2.0%

first ⅓ avg 19.1% → last ⅓ avg 21.1%

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

0.16Best rating — mirage 13–5

13–1Biggest win — mirage

10Longest win streak

20–3In matches decided by ≤2 rounds

4Overtime games

Map breakdown

mirageBest map · 71% over 34infernoWeakest map · 38% over 8

Map	Grade	Played	Record	Win rate	Avg rating
mirage	S	34	24–10	71%	0.02
dust2	A	15	9–6	60%	0.05
ancient	A	14	9–5	64%	0.04
nuke	B	12	6–6	50%	0.03
cache	S	10	7–3	70%	0.04
inferno	C	8	3–5	38%	0.04
anubis	—	4	3–1	75%	0.00
boulder	—	1	1–0	100%	0.06
overpass	—	1	0–1	0%	0.07
train	—	1	1–0	100%	-0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 8). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

7,972Matches

59%Win rate

1.46Avg K/D

93.1ADR

38%Headshot %

Clutches & streaks

42%1v1 clutch win

23%1v2 clutch win

33Longest win streak

Recent Faceit resultsWWWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	863	61%	1.55	19.4
Ancient	531	59%	1.52	18.4
Dust2	263	57%	1.39	18.3
Anubis	217	53%	1.42	18.4
Vertigo	211	68%	1.70	19.2
Nuke	123	59%	1.41	18.6
Overpass	119	61%	1.39	18.1
Train	75	52%	1.64	18.9

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Inventory

$15,830Inventory value99ItemsFull inventory breakdown →

$1,805

$1,770

$1,200

$921

$792

$726

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

19.7%Headshot accuracy

41.4%Accuracy (enemy spotted)

39.4%Spray accuracy

89.4%Counter-strafing

6.4°Preaim

434msReaction time

44.2%T opening success

68.3%CT opening success

0.74Enemies flashed / flash

10.7%Flash assists

12.52HE damage / grenade

16.93Flashes / 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.

38% win rate across 8 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
mirage	13–1	0.08	17%	23 Aug →
dust2	10–13	0.11	14%	15 Aug →
boulder	13–10	0.06	19%	13 Aug →
mirage	2–13	-0.08	53%	11 Aug →
dust2	3–13	0.03	31%	11 Aug →
cache	13–9	0.14	24%	11 Aug →
dust2	8–13	0.05	31%	9 Aug →
nuke	5–13	0.01	22%	9 Aug →
mirage	9–13	0.04	20%	7 Aug →
cache	11–13	-0.00	11%	7 Aug →
cache	13–1	0.05	22%	7 Aug →
mirage	13–6	-0.06	14%	7 Aug →
cache	13–1	0.05	22%	7 Aug →
cache	8–13	0.03	9%	4 Aug →
mirage	31–29	-0.01	16%	29 Jul →
mirage	9–13	0.03	14%	25 Jul →
anubis	5–13	-0.04	22%	25 Jul →
mirage	3–0	0.11	27%	24 Jul →
mirage	10–3	0.08	16%	24 Jul →
inferno	13–10	0.08	15%	24 Jul →
ancient	5–13	0.07	14%	24 Jul →
mirage	13–11	0.03	21%	23 Jul →
nuke	16–14	0.02	24%	23 Jul →
inferno	8–13	0.01	12%	22 Jul →
ancient	13–10	0.04	24%	22 Jul →
mirage	6–13	-0.02	16%	22 Jul →
cache	13–7	0.03	26%	16 Jul →
ancient	5–13	0.05	26%	26 Jun →
mirage	8–13	-0.01	20%	26 Jun →
dust2	13–11	0.01	14%	25 Jun →
nuke	13–8	0.06	28%	25 Jun →
mirage	13–5	0.16	19%	25 Jun →
nuke	13–4	0.07	33%	25 Jun →
nuke	5–13	-0.04	14%	23 Jun →
mirage	8–13	-0.04	7%	23 Jun →
inferno	13–11	0.04	10%	21 Jun →
dust2	4–13	-0.06	4%	20 Jun →
nuke	2–13	-0.06	18%	20 Jun →
ancient	5–13	-0.01	12%	19 Jun →
mirage	6–13	-0.01	16%	19 Jun →
dust2	13–11	0.03	18%	18 Jun →
mirage	13–8	0.05	33%	18 Jun →
nuke	6–13	0.02	32%	18 Jun →
mirage	13–4	0.10	23%	16 Jun →
nuke	7–13	0.01	22%	16 Jun →
mirage	4–13	-0.03	14%	16 Jun →
dust2	13–11	0.02	29%	15 Jun →
nuke	13–8	0.05	29%	15 Jun →
ancient	13–11	0.03	8%	15 Jun →
overpass	8–13	0.07	28%	14 Jun →
dust2	13–5	0.00	17%	14 Jun →
mirage	13–4	0.07	32%	14 Jun →
cache	13–5	0.04	16%	10 Jun →
ancient	13–11	0.05	17%	8 Jun →
inferno	5–13	0.02	31%	6 Jun →
ancient	12–16	0.01	22%	6 Jun →
inferno	8–13	0.10	33%	27 May →
mirage	13–10	0.11	24%	27 May →
ancient	7–13	-0.04	25%	22 May →
ancient	13–5	0.04	5%	21 May →
mirage	3–13	0.04	24%	21 May →
ancient	13–2	0.07	0%	21 May →
inferno	13–11	0.03	18%	21 May →
mirage	0–2	-0.12	0%	18 May →
cache	13–8	-0.01	20%	18 May →
ancient	13–10	0.04	14%	18 May →
cache	13–11	-0.02	16%	14 May →
ancient	13–6	0.07	16%	9 May →
ancient	16–12	0.04	17%	9 May →
cache	11–13	0.07	27%	4 May →
dust2	8–13	0.05	30%	2 May →
anubis	13–11	0.01	19%	2 May →
mirage	13–8	-0.06	13%	2 May →
mirage	13–8	-0.06	13%	2 May →
dust2	8–13	0.05	30%	2 May →
anubis	13–11	0.01	19%	2 May →
mirage	1–0	0.00	0%	2 May →
mirage	13–5	0.02	32%	2 May →
dust2	13–8	0.15	26%	2 May →
inferno	10–13	0.02	21%	2 May →
mirage	1–0	0.00	0%	2 May →
mirage	13–5	0.02	32%	2 May →
dust2	13–8	0.15	26%	2 May →
inferno	10–13	0.02	21%	2 May →
nuke	13–11	0.09	26%	1 May →
nuke	13–11	0.09	26%	1 May →
mirage	13–6	0.03	21%	1 May →
mirage	13–6	0.03	21%	1 May →
mirage	13–11	-0.05	5%	1 May →
mirage	13–11	-0.05	5%	1 May →
mirage	13–8	-0.01	19%	27 Apr →
anubis	13–9	0.04	19%	27 Apr →
ancient	13–5	0.07	29%	24 Apr →
train	13–11	-0.01	24%	22 Apr →
nuke	5–13	-0.00	15%	22 Apr →
dust2	13–6	0.05	10%	20 Apr →
mirage	13–2	0.11	16%	20 Apr →
mirage	13–2	0.11	16%	20 Apr →
dust2	13–6	0.05	10%	20 Apr →
dust2	13–4	0.09	24%	20 Apr →