Ложка дёгтя — CS2 Stats

76561198084653329[U:1:124387601]✓ No bans

1,112Tracked matches62%Win rate2023Tracked since

1,471Hours in CS

CSDB Rating5.5 SolidPassive Rifler

Premier CS Rating18,548Purple band · top ~14.3% of ranked players (population est.)

CSDB Leaderboard#24082 of 52018 tracked

FaceitLevel 4 · 1,083 ELOTop 81.0% of ranked FACEIT players

WingmanMaster Guardian II

Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 4 among CSDB-tracked players (n=1,711), 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 4 median	Level 5 median	vs Level 5
Headshot rate	40.8%	42.7%	44.0%	3.2% short
Shot accuracy	8.3%	10.8%	11.6%	3.4% short
Kill/death ratio	0.95	1.00	1.03	0.08 short
Match win rate	43.3%	44.1%	45.1%	1.8% short

This profile sits below the typical Level 5 player on every metric we can compare.

Widest gap: Shot accuracy. That is the metric furthest from the Level 5 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim63

Positioning45

Utility49

0–100 skill scores via Leetify.

Recent form

STEADY50–44–6Last 10050%Win rateLLWWWLWLLW

Last 10 vs previous 10: -20pp win rate · -0.01 avg rating

Player DNA

Primary style: Passive Rifler — Aim-led profile without a single dominant tendency.

Aim6.3

Aggression2.8

Utility4.9

Positioning4.5

Opening Duels0.0

Clutch4.6

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 NiKo 76% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-duel success; 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. 639ms 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

Aim6.3

Positioning4.5

Utility4.9

Mechanics6.8

Opening Duels0.7

Win Impact9.0

Composite 5.5/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.00

first ⅓ avg -0.01 → last ⅓ avg -0.01

Reaction time631ms−22ms

first ⅓ avg 653ms → last ⅓ avg 631ms

Headshot accuracy20.4%−2.1%

first ⅓ avg 22.4% → last ⅓ avg 20.4%

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

0.13Best rating — debris 9–0

13–1Biggest win — inferno

6Longest win streak

L2Current streak

5–10In matches decided by ≤2 rounds

10Overtime games

Map breakdown

ancientBest map · 69% over 16infernoWeakest map · 25% over 16

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	28	15–13	54%	-0.01
ancient	S	16	11–5	69%	-0.00
inferno	D	16	4–12	25%	-0.02
anubis	A	16	9–7	56%	0.01
mirage	C	10	4–6	40%	-0.02
nuke	B	6	3–3	50%	-0.01
cache	—	2	1–1	50%	0.06
vertigo	—	1	0–1	0%	-0.12
eldorado	—	1	0–1	0%	-0.12
debris	—	1	1–0	100%	0.13
train	—	1	0–1	0%	-0.06
office	—	1	1–0	100%	-0.09
overpass	—	1	1–0	100%	0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (25% over 16). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

72,165Lifetime kills

0.95K/D

3,681Matches

43.3%Match win rate

40.8%Headshot %

8.3%Shot accuracy

7,762MVPs

1,471Hours (in match)

4,690Bombs planted

903Bombs defused

Most-used weapons

AK-4717,298

M4A4 / M4A1-S9,934

AWP9,184

Desert Eagle5,850

P2000 / USP-S3,906

Glock-182,746

Knife2,722

MP92,489

P902,256

XM10141,327

Lifetime map wins

9,505dust2

8,020inferno

1,831vertigo

1,057nuke

429train

220office

95aztec

89dust

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

Faceit stats

Combat

154Matches

53%Win rate

1.17Avg K/D

80.3ADR

45%Headshot %

Clutches & streaks

43%1v1 clutch win

28%1v2 clutch win

7Longest win streak

Recent Faceit resultsWLLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	33	58%	1.14	15.9
Dust2	27	48%	1.15	16.6
Ancient	27	48%	1.27	16.4
Inferno	24	50%	1.14	16.2
Anubis	20	60%	1.23	17.1
Train	9	44%	1.08	15.9
Nuke	8	38%	1.10	21.1
Overpass	3	100%	1.50	15.0

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.

19.5%Headshot accuracy

33.3%Accuracy (enemy spotted)

37.4%Spray accuracy

80.7%Counter-strafing

10.6°Preaim

639msReaction time

23.1%T opening success

35.4%CT opening success

0.62Enemies flashed / flash

5.7%Flash assists

11.16HE damage / grenade

6.56Flashes / 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
You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.
T opening duels 23.1406% — below the 40% mark we flag

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.

25% win rate across 16 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	8–13	-0.05	19%	30 Aug →
mirage	5–13	-0.03	4%	30 Aug →
mirage	13–10	-0.03	22%	30 Aug →
ancient	16–13	0.00	22%	30 Aug →
dust2	13–5	-0.05	21%	29 Aug →
dust2	8–13	-0.03	18%	29 Aug →
nuke	13–7	0.01	15%	29 Aug →
inferno	10–13	-0.02	23%	28 Aug →
ancient	7–13	-0.01	19%	28 Aug →
dust2	13–7	0.05	30%	28 Aug →
nuke	7–9	0.05	24%	24 Aug →
anubis	13–5	0.05	15%	24 Aug →
mirage	13–8	-0.08	20%	24 Aug →
dust2	13–8	-0.01	38%	24 Aug →
ancient	13–4	-0.03	11%	23 Aug →
inferno	0–9	-0.23	33%	23 Aug →
inferno	15–15	0.01	16%	22 Aug →
mirage	13–3	0.01	26%	22 Aug →
dust2	13–5	0.02	14%	22 Aug →
inferno	9–1	0.10	19%	22 Aug →
ancient	8–13	0.10	31%	16 Aug →
dust2	13–9	-0.01	14%	16 Aug →
dust2	2–8	-0.03	40%	15 Aug →
inferno	8–13	0.04	26%	15 Aug →
mirage	8–13	-0.03	13%	12 Aug →
dust2	8–13	-0.03	27%	12 Aug →
nuke	9–13	-0.08	13%	10 Aug →
ancient	13–10	-0.04	17%	10 Aug →
anubis	13–7	0.04	16%	9 Aug →
nuke	13–9	0.02	24%	9 Aug →
anubis	13–4	0.01	14%	9 Aug →
ancient	13–6	-0.01	18%	9 Aug →
dust2	16–14	0.04	9%	9 Aug →
dust2	9–13	0.04	18%	9 Aug →
vertigo	7–9	-0.12	14%	9 Aug →
eldorado	1–9	-0.12	5%	9 Aug →
dust2	9–13	-0.01	16%	8 Aug →
anubis	6–13	-0.01	5%	8 Aug →
inferno	15–15	-0.08	19%	7 Aug →
anubis	13–9	0.07	16%	7 Aug →
anubis	13–4	0.03	18%	6 Aug →
dust2	13–5	-0.01	28%	6 Aug →
mirage	11–13	-0.06	16%	5 Aug →
dust2	13–5	-0.00	14%	5 Aug →
dust2	13–7	-0.02	12%	5 Aug →
ancient	13–11	-0.01	24%	2 Aug →
inferno	5–9	-0.12	4%	2 Aug →
anubis	11–13	0.01	23%	2 Aug →
nuke	4–13	-0.05	7%	2 Aug →
inferno	13–1	0.04	19%	2 Aug →
mirage	12–16	-0.00	24%	2 Aug →
ancient	13–10	-0.02	35%	2 Aug →
anubis	13–4	0.01	20%	2 Aug →
dust2	13–5	-0.06	11%	2 Aug →
mirage	11–13	0.00	13%	2 Aug →
anubis	10–13	0.01	27%	1 Aug →
inferno	1–6	-0.02	33%	1 Aug →
ancient	9–13	-0.01	39%	1 Aug →
inferno	6–13	-0.02	11%	19 Jul →
anubis	5–13	-0.01	26%	19 Jul →
ancient	13–11	0.02	10%	19 Jul →
ancient	16–14	-0.05	20%	19 Jul →
cache	15–15	0.05	18%	19 Jul →
inferno	15–15	0.03	14%	19 Jul →
dust2	16–12	0.04	17%	19 Jul →
ancient	13–7	0.00	13%	19 Jul →
ancient	9–13	0.06	14%	19 Jul →
mirage	14–16	0.08	26%	18 Jul →
dust2	4–13	0.01	30%	18 Jul →
ancient	6–13	0.02	18%	14 Jul →
cache	13–7	0.07	26%	14 Jul →
dust2	6–13	0.01	26%	13 Jul →
inferno	8–8	0.08	26%	13 Jul →
anubis	13–7	-0.02	14%	13 Jul →
dust2	11–13	-0.02	8%	11 Jul →
inferno	13–3	0.04	24%	11 Jul →
anubis	11–13	-0.01	26%	11 Jul →
dust2	9–13	-0.07	31%	9 Jul →
nuke	9–6	-0.02	16%	9 Jul →
anubis	13–3	0.06	29%	9 Jul →
dust2	7–13	-0.05	14%	9 Jul →
dust2	13–7	-0.03	19%	9 Jul →
debris	9–0	0.13	57%	8 Jul →
train	10–13	-0.06	26%	8 Jul →
ancient	13–8	-0.08	20%	8 Jul →
dust2	13–3	0.02	17%	8 Jul →
inferno	4–13	-0.07	22%	7 Jul →
office	13–11	-0.09	19%	6 Jul →
anubis	12–12	-0.04	15%	6 Jul →
overpass	13–2	0.01	25%	6 Jul →
mirage	13–4	-0.04	17%	6 Jul →
anubis	11–13	-0.02	8%	6 Jul →
ancient	13–3	0.00	28%	6 Jul →
dust2	13–4	0.02	13%	6 Jul →
anubis	13–9	0.02	23%	6 Jul →
inferno	13–7	-0.04	17%	5 Jul →
dust2	9–13	0.00	23%	5 Jul →
inferno	3–13	-0.06	30%	4 Jul →
dust2	11–13	-0.02	19%	4 Jul →
dust2	13–10	-0.02	29%	4 Jul →