iamDnkn — CS2 Stats

76561198851182976[U:1:890917248]✓ No bans

1,733Tracked matches56%Win rate2023Tracked since

CSDB Rating6.4 SolidClutch Specialist

FaceitLevel 4Top 81.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim67

Positioning64

Utility75

0–100 skill scores via Leetify.

Recent form

HOT55–35–10Last 10055%Win rateWWWWWWWWLW

Last 10 vs previous 10: +60pp win rate · -0.00 avg rating

Player DNA

Primary style: Clutch Specialist — Late-round 1vX conversion well above par.

Aim6.7

Aggression8.0

Utility7.5

Positioning6.4

Opening Duels3.6

Clutch10.0

Effective flashesHigh utility contributionReliable 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 b1t 90% playstyle similarity

Most alike: positioning profile, opening-fight frequency.

Where you differ: higher utility contribution; 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

Strengths

Flashes. 0.81 enemies blinded per flash — utility that consistently lands.

Areas to improve

Reaction time. 594ms 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

Aim6.7

Positioning6.4

Utility7.5

Mechanics6.1

Opening Duels3.6

Win Impact6.9

Composite 6.4/10 (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 rating0.03−0.04

first ⅓ avg 0.07 → last ⅓ avg 0.03

Reaction time594ms−24ms

first ⅓ avg 617ms → last ⅓ avg 594ms

Headshot accuracy21.8%+1.9%

first ⅓ avg 19.8% → last ⅓ avg 21.8%

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

0.19Best rating — vertigo 13–6

13–1Biggest win — anubis

8Longest win streak

W8Current streak

7–7In matches decided by ≤2 rounds

2Overtime games

Map breakdown

anubisBest map · 71% over 7infernoWeakest map · 31% over 13

Map	Grade	Played	Record	Win rate	Avg rating
vertigo	A	54	34–20	63%	0.06
inferno	D	13	4–9	31%	0.00
nuke	C	8	3–5	38%	-0.01
anubis	S	7	5–2	71%	0.06
ancient	—	4	4–0	100%	0.06
cache	—	4	0–4	0%	0.02
overpass	—	4	2–2	50%	0.01
dust2	—	4	2–2	50%	0.01
mirage	—	1	0–1	0%	-0.06
train	—	1	1–0	100%	0.19

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (31% over 13). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1Matches

100%Win rate

1.03Avg K/D

80.0ADR

33%Headshot %

Clutches & streaks

100%1v1 clutch win

0%1v2 clutch win

1Longest win streak

Recent Faceit resultsLLLLW

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.

22.5%Headshot accuracy

35.3%Accuracy (enemy spotted)

34.9%Spray accuracy

77.5%Counter-strafing

11.5°Preaim

594msReaction time

37.9%T opening success

51.2%CT opening success

0.81Enemies flashed / flash

11.1%Flash assists

14.94HE damage / grenade

13.86Flashes / 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 37.9471% — 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.

31% win rate across 13 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
vertigo	13–11	0.02	15%	16 Aug →
inferno	13–8	-0.00	18%	16 Aug →
nuke	16–14	0.02	20%	16 Aug →
ancient	13–11	0.03	14%	16 Aug →
vertigo	13–8	0.05	27%	7 Aug →
vertigo	13–6	0.06	16%	7 Aug →
vertigo	13–8	0.02	15%	6 Aug →
ancient	13–7	0.08	27%	4 Aug →
vertigo	6–13	-0.00	25%	4 Aug →
vertigo	13–7	0.04	22%	1 Aug →
anubis	13–1	0.11	27%	1 Aug →
inferno	13–4	-0.01	14%	1 Aug →
vertigo	3–13	-0.03	31%	31 Jul →
vertigo	12–12	0.04	14%	29 Jul →
vertigo	13–3	0.12	31%	23 Jul →
vertigo	7–13	0.05	22%	22 Jul →
nuke	11–13	-0.03	23%	22 Jul →
vertigo	5–13	0.02	12%	22 Jul →
vertigo	8–13	0.10	26%	22 Jul →
vertigo	2–13	-0.05	14%	21 Jul →
vertigo	13–11	0.09	36%	16 Jul →
mirage	2–13	-0.06	11%	11 Jul →
inferno	8–13	-0.10	21%	11 Jul →
anubis	13–7	0.11	27%	10 Jul →
cache	9–13	-0.02	26%	10 Jul →
vertigo	13–4	0.17	26%	7 Jul →
vertigo	9–13	-0.00	22%	7 Jul →
vertigo	11–13	0.02	37%	29 Jun →
vertigo	12–12	0.03	15%	3 Jun →
vertigo	12–12	0.09	36%	3 Jun →
inferno	15–15	-0.03	0%	2 Jun →
anubis	13–11	-0.01	31%	29 May →
anubis	11–13	0.03	15%	27 May →
cache	9–13	-0.01	11%	9 May →
vertigo	13–8	0.10	15%	9 May →
vertigo	6–13	0.02	13%	9 May →
vertigo	13–1	-0.00	15%	8 May →
cache	9–13	0.01	28%	1 May →
cache	6–13	0.11	29%	1 May →
nuke	13–8	0.07	26%	27 Apr →
nuke	11–13	-0.01	28%	26 Apr →
inferno	13–8	0.08	21%	26 Apr →
vertigo	13–4	0.18	23%	25 Apr →
nuke	13–8	0.04	34%	25 Apr →
inferno	8–13	0.02	10%	24 Apr →
nuke	11–13	-0.06	13%	24 Apr →
inferno	13–10	0.03	20%	24 Apr →
nuke	4–13	-0.04	71%	13 Apr →
overpass	13–5	-0.03	12%	13 Apr →
inferno	2–13	-0.02	12%	13 Apr →
vertigo	13–3	0.01	17%	12 Apr →
vertigo	13–7	-0.01	18%	11 Apr →
dust2	3–13	-0.02	10%	11 Apr →
dust2	13–9	0.04	24%	1 Apr →
inferno	12–12	0.05	13%	1 Apr →
inferno	11–13	-0.03	15%	23 Mar →
inferno	4–13	0.04	15%	23 Mar →
dust2	3–13	-0.03	26%	19 Mar →
vertigo	10–13	0.05	28%	18 Mar →
anubis	12–12	0.03	32%	18 Mar →
overpass	5–13	-0.01	28%	18 Mar →
dust2	13–11	0.05	32%	17 Mar →
anubis	6–3	0.07	25%	16 Mar →
overpass	13–6	0.08	15%	16 Mar →
vertigo	13–8	0.03	15%	15 Mar →
vertigo	13–7	-0.06	14%	14 Mar →
anubis	8–3	0.06	38%	14 Mar →
train	8–2	0.19	24%	14 Mar →
ancient	13–1	0.13	18%	14 Mar →
overpass	0–4	0.01	50%	14 Mar →
vertigo	13–5	0.09	15%	9 Mar →
vertigo	13–3	0.15	11%	9 Mar →
vertigo	13–9	0.08	17%	7 Mar →
vertigo	12–12	0.10	21%	6 Mar →
vertigo	9–13	-0.02	17%	6 Mar →
vertigo	12–12	0.16	14%	20 Feb →
vertigo	13–7	0.14	22%	20 Feb →
vertigo	9–13	0.02	11%	20 Feb →
vertigo	5–13	-0.01	15%	20 Feb →
vertigo	13–4	0.09	30%	19 Feb →
vertigo	12–12	0.09	20%	18 Feb →
vertigo	13–7	0.06	21%	11 Feb →
vertigo	13–2	-0.01	16%	11 Feb →
vertigo	13–7	0.04	21%	11 Feb →
vertigo	13–11	0.13	16%	10 Feb →
vertigo	13–10	0.06	31%	10 Feb →
inferno	11–13	0.06	22%	1 Feb →
inferno	10–13	-0.03	5%	30 Jan →
vertigo	13–6	0.04	21%	30 Jan →
vertigo	12–12	0.07	20%	30 Jan →
vertigo	13–8	-0.01	16%	30 Jan →
vertigo	13–9	0.06	7%	29 Jan →
ancient	13–10	-0.01	13%	29 Jan →
vertigo	13–9	0.10	21%	28 Jan →
vertigo	13–3	0.13	24%	28 Jan →
nuke	5–8	-0.03	8%	26 Jan →
vertigo	13–1	0.11	25%	26 Jan →
vertigo	13–9	0.07	23%	26 Jan →
vertigo	13–7	0.12	35%	26 Jan →
vertigo	13–6	0.19	24%	26 Jan →