Dølle — CS2 Stats

DK76561198072562765[U:1:112297037]Steam profile ↗VAC banned

564Tracked matches44%Win rate2020Tracked since

CSDB Rating5.0 DevelopingAggressive Rifler

FaceitLevel 6 · 1,249 ELOTop 54.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim79

Positioning59

Utility34

0–100 skill scores via Leetify.

Recent form

COLD46–42–12Last 10046%Win rateLLLLTLWWTW

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

Player DNA

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

Aim7.9

Aggression8.2

Utility3.4

Positioning5.9

Opening Duels3.3

Clutch3.6

Limited utility dependence

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 b1t 89% playstyle similarity

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

Where you differ: lower aim profile; 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

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. 581ms 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

Aim7.9

Positioning5.9

Utility3.4

Mechanics5.9

Opening Duels3.3

Win Impact3.0

Composite 5.0/10 (Developing), 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 rating0.00+0.01

first ⅓ avg -0.01 → last ⅓ avg 0.00

Reaction time600ms−13ms

first ⅓ avg 613ms → last ⅓ avg 600ms

Headshot accuracy29.0%+4.7%

first ⅓ avg 24.3% → last ⅓ avg 29.0%

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

0.15Best rating — dust2 13–5

13–0Biggest win — ancient

5Longest win streak

L4Current streak

5–4In matches decided by ≤2 rounds

3Overtime games

Map breakdown

ancientBest map · 57% over 14infernoWeakest map · 33% over 6

Map	Grade	Played	Record	Win rate	Avg rating
cache	C	23	10–13	43%	0.01
nuke	B	18	9–9	50%	-0.01
ancient	A	14	8–6	57%	-0.01
dust2	B	12	6–6	50%	-0.00
mirage	C	12	5–7	42%	-0.02
inferno	D	6	2–4	33%	-0.01
train	B	6	3–3	50%	0.01
anubis	—	4	2–2	50%	-0.03
overpass	—	3	1–2	33%	-0.01
vertigo	—	1	0–1	0%	-0.07
agency	—	1	0–1	0%	-0.06

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 6). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

311Matches

57%Win rate

1.20Avg K/D

83.7ADR

49%Headshot %

Clutches & streaks

38%1v1 clutch win

22%1v2 clutch win

9Longest win streak

Recent Faceit resultsWWWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	35	57%	1.29	16.8
Nuke	29	66%	1.20	17.9
Ancient	23	65%	1.05	15.0
Inferno	18	56%	1.10	16.8
Train	13	54%	1.27	15.2
Vertigo	13	62%	1.00	19.4
Overpass	12	50%	1.06	17.6
Dust2	6	50%	1.38	14.8

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.

28.9%Headshot accuracy

30.2%Accuracy (enemy spotted)

36.0%Spray accuracy

76.5%Counter-strafing

7.7°Preaim

581msReaction time

49.7%T opening success

36.5%CT opening success

0.42Enemies flashed / flash

6.0%Flash assists

6.50HE damage / grenade

3.99Flashes / 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 0.4176 — below the 0.5 mark we flag
Grenade Lineups →
Advanced Mechanics
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 36.4624% — 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.

33% win rate across 6 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
cache	8–13	0.03	29%	28 Jul →
dust2	9–13	0.02	32%	16 Jul →
mirage	3–13	-0.04	37%	16 Jul →
cache	7–13	-0.07	17%	31 May →
cache	12–12	0.01	50%	31 May →
cache	10–13	-0.05	42%	19 May →
cache	13–8	-0.01	34%	19 May →
cache	13–11	0.01	22%	18 May →
cache	12–12	0.01	33%	18 May →
cache	5–0	0.11	50%	18 May →
cache	6–13	-0.05	44%	17 May →
cache	13–10	-0.01	18%	17 May →
cache	12–7	0.01	23%	14 May →
cache	13–9	-0.01	26%	14 May →
cache	12–12	0.04	22%	12 May →
cache	8–13	0.01	19%	12 May →
cache	12–12	0.07	25%	6 May →
cache	13–8	0.09	17%	5 May →
cache	9–13	-0.00	29%	4 May →
cache	13–4	-0.05	43%	4 May →
cache	10–13	-0.02	26%	4 May →
cache	13–5	-0.03	17%	3 May →
cache	13–1	0.10	23%	3 May →
cache	3–13	-0.03	15%	3 May →
cache	12–12	0.03	37%	29 Apr →
nuke	5–13	-0.04	50%	18 Mar →
ancient	0–13	-0.04	30%	18 Mar →
inferno	9–13	0.01	28%	9 Mar →
mirage	13–11	-0.03	22%	9 Mar →
ancient	7–13	-0.06	24%	22 Feb →
nuke	13–11	0.09	21%	22 Feb →
mirage	5–13	-0.03	17%	17 Feb →
nuke	4–0	-0.01	33%	17 Feb →
nuke	6–13	-0.03	25%	15 Feb →
nuke	7–13	-0.03	30%	28 Jan →
nuke	13–7	-0.01	52%	27 Jan →
mirage	8–13	-0.01	17%	27 Jan →
dust2	13–9	-0.04	28%	26 Jan →
ancient	8–3	-0.01	38%	26 Jan →
ancient	13–5	-0.06	33%	26 Jan →
nuke	15–15	-0.04	20%	26 Jan →
ancient	4–13	0.03	23%	22 Jan →
dust2	13–9	0.09	27%	22 Jan →
nuke	12–12	-0.04	21%	21 Jan →
dust2	10–13	-0.07	9%	20 Jan →
mirage	9–13	-0.03	23%	19 Jan →
ancient	13–0	0.04	8%	19 Jan →
train	13–3	0.10	36%	17 Jan →
ancient	16–12	-0.03	39%	17 Jan →
train	8–13	0.05	38%	16 Jan →
inferno	7–13	-0.03	32%	16 Jan →
overpass	5–13	-0.08	13%	10 Jan →
ancient	13–7	0.01	12%	6 Jan →
nuke	13–8	0.04	18%	6 Jan →
inferno	13–10	0.07	39%	6 Jan →
ancient	0–4	-0.07	0%	5 Jan →
overpass	15–15	-0.01	35%	5 Jan →
mirage	13–10	0.01	12%	4 Jan →
ancient	13–6	0.03	33%	4 Jan →
train	13–3	0.12	54%	4 Jan →
ancient	10–13	-0.10	30%	4 Jan →
anubis	13–9	-0.03	45%	3 Jan →
mirage	13–8	-0.03	38%	3 Jan →
train	13–6	-0.07	26%	3 Jan →
nuke	11–13	-0.05	30%	30 Dec →
train	10–13	-0.05	34%	9 Dec →
nuke	13–10	0.08	20%	16 Oct →
vertigo	4–13	-0.07	44%	21 Sept →
dust2	13–8	0.00	26%	13 Sept →
anubis	12–12	-0.06	20%	27 Aug →
nuke	13–5	0.02	24%	20 Aug →
nuke	10–13	-0.09	32%	18 Aug →
nuke	5–13	-0.04	23%	22 Jul →
overpass	13–6	0.06	22%	5 Jul →
train	1–13	-0.06	22%	5 Jul →
dust2	13–8	-0.02	26%	2 Jun →
mirage	12–12	0.02	38%	31 May →
dust2	6–13	-0.08	21%	18 May →
agency	8–13	-0.06	9%	17 May →
ancient	13–9	0.06	12%	16 May →
nuke	11–13	-0.05	27%	16 May →
ancient	13–3	0.08	16%	13 May →
mirage	12–12	-0.03	26%	24 Apr →
inferno	11–13	-0.02	29%	24 Apr →
inferno	2–9	-0.07	33%	24 Apr →
anubis	13–11	-0.05	21%	16 Apr →
ancient	7–13	-0.05	14%	13 Apr →
dust2	7–13	-0.05	7%	12 Apr →
nuke	13–11	-0.01	19%	31 Mar →
dust2	13–5	0.15	23%	31 Mar →
nuke	13–9	-0.01	33%	23 Mar →
mirage	13–9	-0.07	30%	19 Mar →
inferno	13–9	0.00	13%	11 Mar →
dust2	5–13	-0.04	13%	10 Mar →
mirage	13–8	0.01	35%	28 Feb →
anubis	12–12	0.01	20%	25 Feb →
dust2	11–13	-0.02	30%	25 Feb →
mirage	10–13	0.04	41%	23 Feb →
nuke	13–6	0.10	28%	23 Feb →
dust2	13–8	0.04	26%	17 Feb →