Dizzmark — CS2 Stats

76561199147543521[U:1:1187277793]1 game ban

1,778Tracked matches77%Win rate2021Tracked since

CSDB Rating7.4 StrongAggressive Rifler

Premier CS Rating26,488Top 10% of 17,162 CSDB-tracked playersRed band · top ~2.3% of ranked players (population est.)

CSDB Leaderboard#1617 of 22097 tracked

FaceitLevel 10 · 2,219 ELOTop 12.4% of ranked FACEIT players

WingmanLegendary Eagle Master

Ladder ranks via Leetify

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Performance scores

Aim86

Positioning48

Utility67

0–100 skill scores via Leetify.

Recent form

STEADY54–42–4Last 10054%Win rateWWLWWWWWLW

Last 10 vs previous 10: -10pp win rate · -0.07 avg rating

Player DNA

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

Aim8.6

Aggression7.9

Utility6.7

Positioning4.8

Opening Duels3.6

Clutch3.4

Sharp aimer

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 92% playstyle similarity

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

Where you differ: lower positioning 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

Aim. Aim score of 86 — the mechanical foundation is a clear strength.

Areas to improve

Positioning. Positioning trails aim by 38 points — deaths here waste a strong aim profile.

Reaction time. 652ms 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

Aim8.6

Positioning4.8

Utility6.7

Mechanics7.5

Opening Duels3.6

Win Impact10.0

Composite 7.4/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.03+0.00

first ⅓ avg 0.02 → last ⅓ avg 0.03

Reaction time655ms−0ms

first ⅓ avg 656ms → last ⅓ avg 655ms

Headshot accuracy27.2%+3.2%

first ⅓ avg 23.9% → last ⅓ avg 27.2%

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

0.21Best rating — train 3–0

13–0Biggest win — mirage

7Longest win streak

W2Current streak

4–6In matches decided by ≤2 rounds

3Overtime games

Map breakdown

dust2Best map · 63% over 30infernoWeakest map · 38% over 8

Map	Grade	Played	Record	Win rate	Avg rating
mirage	A	37	21–16	57%	0.01
dust2	A	30	19–11	63%	0.02
nuke	A	14	8–6	57%	0.04
inferno	C	8	3–5	38%	0.03
cache	—	3	2–1	67%	0.00
office	—	3	0–3	0%	0.01
anubis	—	2	0–2	0%	0.01
train	—	2	1–1	50%	0.11
ancient	—	1	0–1	0%	-0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 8). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,533Matches

50%Win rate

1.10Avg K/D

81.7ADR

49%Headshot %

Clutches & streaks

37%1v1 clutch win

23%1v2 clutch win

11Longest win streak

Recent Faceit resultsLWLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	424	57%	1.16	16.6
Dust2	194	53%	1.10	16.6
Ancient	145	41%	0.98	15.8
Inferno	104	46%	1.07	16.7
Anubis	103	46%	1.06	16.4
Nuke	65	42%	1.12	16.4
Train	33	58%	1.09	14.8
Vertigo	18	33%	1.07	15.7

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.

27.0%Headshot accuracy

37.0%Accuracy (enemy spotted)

44.6%Spray accuracy

83.7%Counter-strafing

8.7°Preaim

652msReaction time

37.1%T opening success

52.0%CT opening success

0.65Enemies flashed / flash

10.5%Flash assists

14.38HE damage / grenade

10.57Flashes / 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 37.1366% — 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.

38% win rate across 8 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	13–9	-0.01	17%	27 Aug →
dust2	13–9	0.01	20%	17 Aug →
mirage	3–13	-0.07	19%	15 Aug →
dust2	13–7	0.08	39%	14 Jul →
mirage	13–7	0.03	41%	14 Jul →
mirage	13–0	-0.02	6%	14 Jul →
nuke	13–10	-0.00	23%	13 Jul →
mirage	13–3	-0.00	39%	13 Jul →
mirage	10–13	-0.09	13%	13 Jul →
dust2	13–1	0.06	65%	13 Jul →
dust2	13–11	0.12	25%	13 Jul →
mirage	13–7	0.04	30%	13 Jul →
dust2	13–10	0.03	15%	13 Jul →
dust2	13–5	0.08	25%	13 Jul →
mirage	13–8	0.05	27%	13 Jul →
mirage	9–13	0.03	21%	13 Jul →
inferno	13–6	0.13	25%	13 Jul →
nuke	13–7	0.10	45%	13 Jul →
mirage	13–6	0.01	21%	13 Jul →
nuke	13–10	0.06	45%	13 Jul →
nuke	13–0	0.10	26%	13 Jul →
inferno	7–13	0.02	20%	12 Jul →
mirage	13–10	0.02	17%	12 Jul →
cache	13–6	0.02	26%	12 Jul →
dust2	13–6	0.03	23%	12 Jul →
anubis	11–13	0.00	32%	12 Jul →
inferno	8–8	-0.08	25%	12 Jul →
mirage	8–13	0.07	32%	11 Jul →
dust2	13–6	0.09	27%	11 Jul →
mirage	13–3	-0.01	24%	11 Jul →
mirage	6–13	-0.06	29%	11 Jul →
dust2	13–3	0.01	33%	11 Jul →
nuke	5–13	-0.00	21%	11 Jul →
mirage	7–13	-0.04	25%	11 Jul →
dust2	9–13	-0.06	15%	11 Jul →
nuke	13–6	0.11	27%	11 Jul →
mirage	13–3	0.06	31%	11 Jul →
mirage	1–13	-0.03	33%	11 Jul →
mirage	13–6	0.06	29%	11 Jul →
nuke	10–13	0.01	22%	10 Jul →
office	12–12	0.04	24%	9 Jul →
office	11–13	-0.07	34%	9 Jul →
dust2	13–3	0.01	20%	6 Jul →
mirage	13–7	0.06	17%	5 Jul →
dust2	7–13	-0.02	22%	5 Jul →
dust2	13–7	-0.01	38%	4 Jul →
mirage	6–13	-0.04	20%	4 Jul →
mirage	13–7	0.04	24%	29 Jun →
dust2	13–10	-0.02	35%	28 Jun →
nuke	6–13	-0.01	17%	22 Jun →
office	9–13	0.06	14%	21 Jun →
cache	7–13	0.01	40%	21 Jun →
mirage	2–13	-0.06	14%	18 Jun →
mirage	7–13	-0.01	18%	17 Jun →
mirage	13–8	0.00	16%	17 Jun →
dust2	13–5	0.04	30%	16 Jun →
dust2	13–10	-0.05	24%	24 May →
mirage	13–5	0.06	41%	24 May →
nuke	16–13	0.02	19%	14 May →
cache	13–11	-0.02	22%	14 May →
nuke	13–2	0.10	24%	12 May →
inferno	4–13	0.02	22%	12 May →
dust2	13–8	0.06	30%	12 May →
nuke	12–16	0.02	18%	6 May →
nuke	13–8	0.02	28%	5 May →
mirage	3–13	-0.06	21%	30 Apr →
dust2	9–13	0.01	29%	28 Apr →
ancient	7–13	-0.04	17%	28 Apr →
anubis	10–13	0.02	16%	22 Apr →
dust2	5–13	-0.01	23%	22 Apr →
train	12–12	0.01	23%	22 Apr →
train	3–0	0.21	0%	22 Apr →
inferno	9–6	0.04	27%	20 Apr →
inferno	7–9	0.06	41%	20 Apr →
mirage	6–13	-0.00	20%	18 Apr →
mirage	13–11	0.00	15%	17 Apr →
dust2	9–13	0.02	25%	16 Apr →
dust2	13–3	-0.05	26%	16 Apr →
dust2	6–8	-0.09	33%	16 Apr →
dust2	6–13	-0.01	42%	15 Apr →
mirage	13–5	0.06	15%	15 Apr →
inferno	10–13	-0.00	30%	15 Apr →
inferno	13–9	0.05	23%	13 Apr →
mirage	13–10	0.00	16%	13 Apr →
mirage	11–13	-0.02	17%	11 Apr →
nuke	13–16	0.02	29%	11 Apr →
mirage	13–6	0.03	20%	11 Apr →
dust2	13–7	0.01	35%	30 Mar →
nuke	9–13	-0.05	19%	30 Mar →
dust2	6–13	-0.02	33%	26 Mar →
mirage	12–12	-0.00	21%	25 Mar →
dust2	9–13	-0.00	25%	23 Mar →
dust2	11–13	0.01	18%	22 Mar →
mirage	7–13	-0.01	22%	22 Mar →
dust2	13–7	0.10	30%	16 Mar →
mirage	13–8	0.03	22%	16 Mar →
mirage	10–13	0.08	31%	16 Mar →
dust2	3–13	0.15	33%	16 Mar →
mirage	13–8	0.06	25%	15 Mar →
dust2	13–11	0.07	15%	15 Mar →