✡︎ Shabbos Kestenstein ✡ — CS2 Stats

CA76561198151596874[U:1:191331146]Steam profile ↗✓ No bans

2,110Tracked matches43%Win rate2020Tracked since

2,335Hours in CS6Hrs last 2 wks

CSDB Rating6.0 SolidAggressive Rifler

FaceitLevel 3Top 90.6% of ranked FACEIT players

WingmanSupreme Master First Class

Ladder ranks via Leetify

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Performance scores

Aim89

Positioning64

Utility5

0–100 skill scores via Leetify.

Recent form

STEADY54–33–13Last 10054%Win rateLWLWLWLWLW

Last 10 vs previous 10: +20pp win rate · +0.00 avg rating

Player DNA

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

Aim8.9

Aggression9.2

Utility0.5

Positioning6.4

Opening Duels4.9

Clutch10.0

Sharp aimerLimited utility dependenceReliable 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 donk 85% playstyle similarity

Most alike: opening-duel success, opening-fight frequency.

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 89 — the mechanical foundation is a clear strength.

Areas to improve

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

Reaction time. 562ms 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

Aim8.9

Positioning6.4

Utility0.5

Mechanics8.4

Opening Duels4.9

Win Impact2.6

Composite 6.0/10 (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 rating0.08−0.02

first ⅓ avg 0.10 → last ⅓ avg 0.08

Reaction time562ms−7ms

first ⅓ avg 569ms → last ⅓ avg 562ms

Headshot accuracy26.0%−1.9%

first ⅓ avg 27.9% → last ⅓ avg 26.0%

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

0.24Best rating — office 12–12

13–2Biggest win — mirage

10Longest win streak

3–3In matches decided by ≤2 rounds

Map breakdown

vertigoBest map · 77% over 13anubisWeakest map · 25% over 8

Map	Grade	Played	Record	Win rate	Avg rating
vertigo	S	13	10–3	77%	0.15
office	D	10	3–7	30%	0.10
dust2	S	10	7–3	70%	0.10
nuke	C	9	4–5	44%	0.07
ancient	A	9	5–4	56%	0.09
anubis	D	8	2–6	25%	0.09
train	B	6	3–3	50%	0.10
cache	S	6	4–2	67%	0.11
boulder	A	5	3–2	60%	0.10
shelter	A	5	3–2	60%	0.07
inferno	C	5	2–3	40%	0.03
overpass	—	4	3–1	75%	0.13
mirage	—	4	3–1	75%	0.12
fachwerk	—	3	1–2	33%	0.04
italy	—	3	1–2	33%	0.10

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (25% over 8). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

61,549Lifetime kills

1.40K/D · Top 10% of tracked players

2,810Matches

51.4%Match win rate · Top 25% of tracked players

50.8%Headshot % · Top 50% of tracked players

9.2%Shot accuracy

9,488MVPs

951Hours (in match)

1,186Bombs planted

694Bombs defused

Most-used weapons

AK-4721,267

M4A4 / M4A1-S11,910

AWP4,602

P2000 / USP-S3,701

Glock-183,274

MP72,166

Desert Eagle1,845

SCAR-201,515

MP91,073

SSG 081,072

Lifetime map wins

3,747dust2

2,438inferno

2,085vertigo

1,504office

1,453nuke

868train

225italy

68cbble

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

Faceit stats

Combat

98Matches

49%Win rate

1.25Avg K/D

113.3ADR

42%Headshot %

Clutches & streaks

100%1v1 clutch win

0%1v2 clutch win

9Longest win streak

Recent Faceit resultsLWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	4	25%	1.18	19.5
Inferno	2	100%	2.36	22.5
Ancient	2	100%	1.22	17.0
Vertigo	1	0%	0.93	13.0
Nuke	1	100%	1.45	16.0

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.

25.4%Headshot accuracy

40.1%Accuracy (enemy spotted)

34.1%Spray accuracy

87.9%Counter-strafing

9.0°Preaim

562msReaction time

44.2%T opening success

55.0%CT opening success

0.16Enemies flashed / flash

0.0%Flash assists

0.12HE damage / grenade

0.63Flashes / 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 0.1577 — 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.

25% win rate across 8 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
boulder	9–13	0.03	25%	28 Aug →
anubis	11–4	0.16	14%	24 Aug →
overpass	7–13	0.01	22%	24 Aug →
nuke	13–7	0.06	25%	23 Aug →
vertigo	7–13	0.05	17%	18 Aug →
anubis	13–11	0.21	20%	18 Aug →
train	7–13	-0.02	33%	18 Aug →
ancient	13–8	0.08	23%	18 Aug →
fachwerk	10–13	0.04	20%	11 Aug →
office	13–5	0.11	17%	11 Aug →
anubis	7–13	0.04	23%	11 Aug →
dust2	8–13	0.01	28%	11 Aug →
shelter	5–13	-0.03	49%	11 Aug →
ancient	11–5	0.14	38%	10 Aug →
vertigo	13–4	0.24	32%	10 Aug →
cache	9–13	0.04	21%	10 Aug →
ancient	13–3	0.13	24%	10 Aug →
anubis	10–13	0.03	21%	9 Aug →
italy	12–12	0.06	18%	9 Aug →
anubis	2–13	0.06	20%	9 Aug →
overpass	12–6	0.14	20%	9 Aug →
vertigo	13–9	0.11	24%	9 Aug →
inferno	2–13	0.08	28%	9 Aug →
office	12–12	0.14	25%	9 Aug →
vertigo	11–13	0.18	21%	9 Aug →
anubis	6–13	0.07	31%	9 Aug →
office	11–13	0.07	34%	8 Aug →
boulder	6–13	-0.02	33%	8 Aug →
shelter	13–8	0.12	31%	8 Aug →
nuke	12–3	0.06	36%	8 Aug →
mirage	13–4	0.17	36%	8 Aug →
ancient	7–13	0.09	24%	8 Aug →
train	13–8	0.08	27%	8 Aug →
vertigo	13–5	0.06	20%	8 Aug →
boulder	13–10	0.14	23%	8 Aug →
inferno	13–9	0.10	25%	7 Aug →
dust2	3–13	0.13	38%	7 Aug →
office	13–10	0.17	40%	7 Aug →
ancient	12–12	0.01	19%	5 Aug →
nuke	7–13	0.01	13%	5 Aug →
dust2	13–10	0.10	21%	5 Aug →
inferno	4–13	-0.05	33%	4 Aug →
inferno	13–8	0.10	29%	3 Aug →
inferno	1–13	-0.06	22%	3 Aug →
mirage	13–2	0.11	24%	2 Aug →
ancient	8–13	0.10	37%	1 Aug →
ancient	13–10	0.02	45%	1 Aug →
dust2	13–11	0.15	24%	1 Aug →
boulder	13–5	0.16	35%	1 Aug →
vertigo	13–9	0.17	26%	31 Jul →
shelter	13–5	0.14	35%	31 Jul →
train	13–5	0.17	18%	31 Jul →
office	12–12	0.06	37%	31 Jul →
vertigo	13–7	0.19	34%	31 Jul →
cache	13–11	0.17	20%	31 Jul →
dust2	2–6	0.11	42%	31 Jul →
office	13–8	0.05	12%	31 Jul →
dust2	13–4	0.16	31%	31 Jul →
boulder	13–4	0.20	38%	30 Jul →
overpass	13–3	0.17	15%	30 Jul →
ancient	13–2	0.17	15%	30 Jul →
shelter	13–4	0.03	39%	29 Jul →
dust2	13–2	0.10	14%	29 Jul →
vertigo	13–5	0.16	17%	29 Jul →
vertigo	13–7	0.14	22%	29 Jul →
mirage	13–7	0.15	15%	26 Jul →
train	12–12	0.14	21%	26 Jul →
dust2	13–7	0.10	27%	26 Jul →
office	10–13	0.10	44%	21 Jul →
nuke	7–13	0.07	20%	18 Jul →
office	3–13	0.03	44%	18 Jul →
fachwerk	9–13	0.01	24%	18 Jul →
shelter	6–13	0.08	26%	18 Jul →
vertigo	13–5	0.10	17%	18 Jul →
nuke	11–13	0.10	31%	18 Jul →
italy	13–3	0.20	37%	17 Jul →
train	13–8	0.15	25%	17 Jul →
dust2	13–2	0.00	22%	17 Jul →
nuke	13–10	0.01	27%	17 Jul →
ancient	12–12	0.04	17%	17 Jul →
cache	12–12	0.09	36%	17 Jul →
vertigo	13–3	0.18	26%	17 Jul →
fachwerk	13–4	0.08	25%	17 Jul →
office	12–12	0.03	32%	17 Jul →
overpass	13–10	0.19	21%	17 Jul →
mirage	0–6	0.04	33%	16 Jul →
cache	13–6	0.15	37%	16 Jul →
anubis	12–12	0.09	29%	16 Jul →
nuke	9–0	0.10	37%	16 Jul →
italy	12–12	0.05	26%	16 Jul →
vertigo	13–4	0.14	27%	16 Jul →
office	12–12	0.24	34%	14 Jul →
nuke	4–13	0.04	20%	14 Jul →
cache	13–5	0.14	32%	14 Jul →
vertigo	12–12	0.18	30%	14 Jul →
dust2	13–9	0.14	19%	14 Jul →
anubis	7–13	0.03	19%	13 Jul →
nuke	6–13	0.23	23%	13 Jul →
cache	13–5	0.10	29%	13 Jul →
train	12–12	0.10	23%	13 Jul →