Bazaazz — CS2 Stats

DK76561198824951626[U:1:864685898]Steam profile ↗✓ No bans

860Tracked matches40%Win rate2021Tracked since

CSDB Rating5.4 DevelopingHybrid Rifler

FaceitLevel 6Top 54.0% of ranked FACEIT players

WingmanGold Nova Master

Ladder ranks via Leetify

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Performance scores

Aim67

Positioning62

Utility56

0–100 skill scores via Leetify.

Recent form

STEADY47–52–1Last 10047%Win rateWLLLWLLWWL

Last 10 vs previous 10: +10pp win rate · +0.02 avg rating

Player DNA

Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.

Aim6.7

Aggression9.0

Utility5.6

Positioning6.2

Opening Duels3.7

Strong CT-side opener

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 jL 91% playstyle similarity

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

Where you differ: 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

T-side openings. Opening success drops from 55% on CT to 35% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 639ms 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

Positioning6.2

Utility5.6

Mechanics5.4

Opening Duels3.7

Win Impact1.7

Composite 5.4/10 (Developing), 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 rating0.01−0.01

first ⅓ avg 0.01 → last ⅓ avg 0.01

Reaction time642ms−7ms

first ⅓ avg 649ms → last ⅓ avg 642ms

Headshot accuracy16.3%+2.7%

first ⅓ avg 13.6% → last ⅓ avg 16.3%

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

0.14Best rating — anubis 13–4

13–1Biggest win — overpass

8Longest win streak

13–14In matches decided by ≤2 rounds

11Overtime games

Map breakdown

ancientBest map · 57% over 21infernoWeakest map · 35% over 17

Map	Grade	Played	Record	Win rate	Avg rating
ancient	A	21	12–9	57%	0.03
overpass	C	17	7–10	41%	-0.01
inferno	C	17	6–11	35%	-0.01
nuke	B	15	7–8	47%	0.01
anubis	B	13	7–6	54%	0.02
dust2	C	7	3–4	43%	0.01
cache	—	4	1–3	25%	-0.02
mirage	—	3	2–1	67%	-0.01
train	—	2	1–1	50%	0.02
vertigo	—	1	1–0	100%	0.12

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (35% over 17). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

222Matches

51%Win rate

0.98Avg K/D

—ADR

30%Headshot %

Clutches & streaks

—1v1 clutch win

—1v2 clutch win

9Longest win streak

Recent Faceit resultsLWWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Vertigo	8	62%	1.33	19.8
Ancient	5	40%	1.22	16.2
Inferno	3	33%	1.12	14.3
Anubis	2	0%	0.64	10.0
Mirage	2	0%	0.92	15.5
Overpass	1	100%	1.14	24.0
Dust2	1	0%	1.05	22.0
Nuke	1	100%	2.83	17.0

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.

16.5%Headshot accuracy

36.9%Accuracy (enemy spotted)

43.0%Spray accuracy

74.4%Counter-strafing

9.8°Preaim

639msReaction time

35.0%T opening success

54.9%CT opening success

0.45Enemies flashed / flash

9.0%Flash assists

10.87HE damage / grenade

8.03Flashes / 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 0.4478 — below the 0.5 mark we flag
Grenade Lineups →
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 34.9647% — 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.

35% win rate across 17 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	13–11	-0.00	16%	4 Aug →
anubis	11–13	0.01	12%	4 Aug →
ancient	14–16	0.03	13%	4 Aug →
cache	14–16	-0.01	12%	4 Aug →
nuke	13–5	0.10	16%	5 Jul →
ancient	11–13	-0.02	15%	5 Jul →
anubis	5–13	-0.04	11%	5 Jul →
overpass	13–8	-0.01	11%	5 Jul →
anubis	13–11	-0.01	17%	12 Jun →
overpass	14–16	0.00	10%	12 Jun →
anubis	9–13	-0.02	13%	12 Jun →
inferno	16–14	-0.04	18%	12 Jun →
nuke	7–13	-0.04	9%	8 Jun →
inferno	4–13	0.03	9%	8 Jun →
anubis	13–11	0.01	13%	2 Jun →
ancient	9–13	0.03	15%	24 May →
cache	9–13	-0.04	24%	24 May →
nuke	4–13	-0.06	12%	19 May →
mirage	13–11	0.05	15%	19 May →
overpass	3–13	-0.07	17%	19 May →
cache	6–13	-0.04	26%	19 May →
ancient	13–4	0.12	35%	18 Apr →
nuke	14–16	-0.06	18%	18 Apr →
anubis	13–7	0.08	17%	18 Apr →
anubis	13–4	0.14	29%	18 Apr →
overpass	3–13	-0.03	25%	18 Apr →
ancient	13–7	0.04	22%	18 Apr →
overpass	13–8	0.01	19%	2 Mar →
overpass	10–13	0.00	15%	2 Mar →
anubis	6–13	0.03	23%	2 Mar →
vertigo	9–3	0.12	9%	23 Feb →
anubis	14–16	-0.01	13%	16 Feb →
nuke	13–11	-0.05	10%	16 Feb →
ancient	11–13	-0.04	1%	16 Feb →
inferno	5–13	-0.01	29%	13 Feb →
nuke	4–13	-0.00	40%	13 Feb →
ancient	13–7	-0.02	26%	13 Feb →
anubis	16–14	0.01	11%	13 Feb →
inferno	13–10	-0.01	12%	13 Feb →
nuke	13–2	0.02	11%	2 Feb →
anubis	16–13	0.03	6%	2 Feb →
ancient	16–14	0.01	7%	2 Feb →
anubis	13–11	-0.04	19%	26 Jan →
inferno	13–11	0.04	11%	3 Jan →
overpass	11–13	0.00	11%	3 Jan →
nuke	4–13	-0.03	17%	3 Jan →
overpass	9–13	-0.06	10%	3 Jan →
inferno	0–13	-0.03	13%	3 Jan →
nuke	13–7	0.05	16%	3 Jan →
overpass	11–13	-0.02	17%	3 Jan →
ancient	13–7	0.06	8%	3 Jan →
ancient	9–13	-0.00	10%	8 Dec →
overpass	13–9	0.05	7%	8 Dec →
inferno	13–11	-0.02	14%	8 Dec →
nuke	13–8	0.02	19%	8 Dec →
ancient	13–8	0.01	17%	5 Dec →
inferno	10–13	-0.03	10%	5 Dec →
dust2	5–13	-0.03	11%	5 Dec →
ancient	9–13	-0.00	12%	5 Dec →
overpass	12–12	-0.04	8%	5 Dec →
inferno	5–13	-0.02	13%	1 Dec →
train	16–13	0.07	16%	29 Nov →
dust2	13–11	0.06	12%	29 Nov →
inferno	13–6	-0.07	15%	29 Nov →
overpass	13–11	0.02	11%	28 Nov →
ancient	13–8	0.05	11%	28 Nov →
mirage	8–13	-0.04	12%	28 Nov →
ancient	8–13	0.02	13%	28 Nov →
inferno	10–13	0.03	20%	28 Nov →
nuke	11–13	-0.05	14%	28 Nov →
ancient	13–10	-0.00	13%	28 Nov →
inferno	6–13	-0.00	7%	21 Nov →
ancient	13–10	0.09	14%	21 Nov →
overpass	11–13	-0.01	10%	21 Nov →
dust2	8–13	0.04	9%	21 Nov →
overpass	5–13	0.02	20%	21 Nov →
ancient	3–13	-0.01	11%	21 Nov →
anubis	10–13	0.04	19%	14 Nov →
train	5–13	-0.04	10%	14 Nov →
ancient	13–3	0.10	11%	14 Nov →
overpass	13–1	0.12	16%	14 Nov →
nuke	11–13	0.02	13%	14 Nov →
inferno	12–16	0.01	8%	14 Nov →
nuke	5–13	-0.01	9%	13 Nov →
dust2	6–13	-0.08	16%	13 Nov →
overpass	13–6	-0.01	18%	13 Nov →
inferno	10–13	-0.00	16%	13 Nov →
nuke	13–5	0.06	15%	15 Sept →
inferno	11–13	-0.05	19%	15 Sept →
ancient	13–4	0.03	17%	15 Sept →
dust2	7–13	-0.00	18%	15 Sept →
inferno	7–13	-0.07	20%	3 Sept →
overpass	13–10	-0.06	9%	3 Sept →
dust2	13–2	0.12	21%	3 Sept →
inferno	13–2	0.06	9%	27 Aug →
nuke	8–1	0.14	10%	27 Aug →
mirage	7–2	-0.04	14%	27 Aug →
dust2	13–4	-0.01	16%	27 Aug →
ancient	13–6	-0.03	6%	27 Aug →
ancient	10–13	0.05	9%	23 Jul →