Kolsa | Beer Drinkers' Union — CS2 Stats

76561199147660033[U:1:1187394305]Steam profile ↗✓ No bans

485Tracked matches55%Win rate2021Tracked since

1,183Hours in CS52Hrs last 2 wks

CSDB Rating3.3 Learning

Premier CS Rating3,614Grey band · top ~84.7% of ranked players (population est.)

CSDB Leaderboard#15707 of 20296 tracked

Ladder ranks via Leetify

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Performance scores

Aim32

Positioning33

Utility54

0–100 skill scores via Leetify.

Recent form

STEADY43–53–4Last 10043%Win rateWLLWLWWWLL

Last 10 vs previous 10: -10pp win rate · +0.04 avg rating

Player DNA

Aim3.2

Aggression1.2

Utility5.4

Positioning3.3

Opening Duels0.0

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 NiKo 69% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower opening-fight frequency; 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. 646ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 66% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim3.2

Positioning3.3

Utility5.4

Mechanics3.6

Opening Duels0.0

Win Impact6.7

Composite 3.3/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.01

first ⅓ avg 0.00 → last ⅓ avg -0.01

Reaction time648ms−50ms

first ⅓ avg 698ms → last ⅓ avg 648ms

Headshot accuracy12.6%−0.2%

first ⅓ avg 12.8% → last ⅓ avg 12.6%

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

0.12Best rating — nuke 13–3

13–2Biggest win — nuke

4Longest win streak

7–8In matches decided by ≤2 rounds

5Overtime games

Map breakdown

nukeBest map · 60% over 15infernoWeakest map · 29% over 14

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	28	12–16	43%	-0.02
ancient	C	16	7–9	44%	0.00
nuke	A	15	9–6	60%	0.01
inferno	D	14	4–10	29%	-0.00
mirage	C	8	3–5	38%	0.00
cache	B	8	4–4	50%	-0.03
anubis	B	6	3–3	50%	-0.03
train	—	2	0–2	0%	0.04
fachwerk	—	1	0–1	0%	-0.00
vertigo	—	1	1–0	100%	0.02
office	—	1	0–1	0%	0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (29% over 14). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

30,195Lifetime kills

1.55K/D · Top 5% of tracked players

1,459Matches

61.3%Match win rate · Top 5% of tracked players

33.9%Headshot %

6.8%Shot accuracy

6,085MVPs

532Hours (in match)

3,891Bombs planted

796Bombs defused

Most-used weapons

AK-477,920

AWP4,338

M4A4 / M4A1-S3,770

P2000 / USP-S1,537

Glock-181,190

MP91,103

Desert Eagle1,094

Galil AR954

SG 553892

AUG711

Lifetime map wins

2,256dust2

1,146nuke

1,037inferno

384vertigo

364train

137office

107italy

73aztec

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

Skill profile

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

12.6%Headshot accuracy

31.0%Accuracy (enemy spotted)

36.9%Spray accuracy

66.4%Counter-strafing

12.5°Preaim

646msReaction time

22.7%T opening success

22.9%CT opening success

0.65Enemies flashed / flash

9.8%Flash assists

18.63HE damage / grenade

5.12Flashes / 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 12.516° — 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 12.6036% — below the 15% mark we flag
Aim Training →

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.

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