LuaZo🔝 — CS2 Stats

DE76561198074236655[U:1:113970927]Steam profile ↗✓ No bans

2,361Tracked matches47%Win rate2021Tracked since

CSDB Rating5.7 SolidSupport

Premier CS Rating12,626Blue band · top ~41% of ranked players (population est.)

CSDB Leaderboard#152099 of 233094 tracked

WingmanLegendary Eagle Master

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 11 Sep 2026 (9 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 2,361 tracked matches. Play, then come back: the next observation lands here.

Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 39 days played since 4 May 2026. Come back after the next session and the change shows above.

Is this you? Sign in with Steam to claim it and connect match tracking →

Rating over time

Premier CS Rating: 12,626 +636 20 Jul – 11 Sept · 20 days played

14,999Peak Premier in tracked matches

1,663Highest Faceit ELO seen on CSDB

39Days played since 2026-05-04

Faceit ELO

At peak — 1,663
Next: Level 9 at 1,751 — 88 to go
Reached: Level 8 · Level 7 · Level 6 · Level 5
Level 8 first seen 2026-09-11
Level 7 first seen 2026-09-11

Premier CS Rating

2,173 below peak (14,799)
+9 over 30 days · steady
Next: Purple band at 15,000 — 2,374 to go
Reached: Blue band · Light Blue band
Blue band first seen 2026-09-11
Light Blue band first seen 2026-09-11

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

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Performance scores

Aim64

Positioning64

Utility64

0–100 skill scores via Leetify.

Recent form

COLD47–49–4Last 10047%Win rateLWWLLWLLLL

Last 10 vs previous 10: −10pp win rate · −0.03 avg rating · −0.7pp headshot accuracy · +32ms reaction

Win rate −10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

2–3 · 40% win rate
Avg rating -0.00
Avg headshot accuracy 16%
Avg reaction 574ms

Last 10

3–7 · 30% win rate
Avg rating -0.02
Avg headshot accuracy 14%
Avg reaction 630ms

Last 20

7–13 · 35% win rate
Avg rating -0.00
Avg headshot accuracy 15%
Avg reaction 614ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Support — Utility contribution stands above the rest of this profile (+1.1 against its own average).

Aim6.4

Utility6.4

Positioning6.4

Opening Duels4.7

Clutch3.8

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

Plays most like jL 77% playstyle similarity

Most alike: utility contribution, positioning profile.

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

Reaction time. 626ms 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

Aim6.4

Positioning6.4

Utility6.4

Mechanics6.9

Opening Duels3.7

Win Impact3.9

Composite 5.7/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 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 time612ms−36ms

first ⅓ avg 647ms → last ⅓ avg 612ms

Headshot accuracy15.5%−0.1%

first ⅓ avg 15.7% → last ⅓ avg 15.5%

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.

Personal bests

0.15Best match rating · 13–6 · inferno, 20 Jul →

40%Best headshot accuracy · 13–3 · inferno, 14 Jul →

375msFastest reaction time · 1–4 · ancient, 7 Aug →

13–1Biggest win · ancient, 18 Aug →

Across the last 100 tracked matches.

Highlights

5Longest win streak

8–7In matches decided by ≤2 rounds

12Overtime games

Map breakdown

anubisBest map · 56% over 16infernoWeakest map · 31% over 13

Map	Grade	Played	Record	Win rate	Avg rating
ancient	B	20	9–11	45%	-0.01
anubis	A	16	9–7	56%	0.01
cache	B	15	8–7	53%	0.02
nuke	B	15	8–7	53%	-0.00
inferno	D	13	4–9	31%	0.01
dust2	B	11	5–6	45%	0.01
mirage	D	9	3–6	33%	-0.02
overpass	—	1	1–0	100%	0.01

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

410Matches

50%Win rate

1.09Avg K/D

78.0ADR

41%Headshot %

Clutches & streaks

39%1v1 clutch win

20%1v2 clutch win

10Longest win streak

Recent Faceit resultsLWWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	88	45%	1.03	16.1
Anubis	63	51%	1.11	15.8
Mirage	61	38%	1.01	14.5
Nuke	45	51%	1.15	15.9
Inferno	28	61%	0.97	13.5
Overpass	27	63%	1.25	16.2
Train	24	46%	1.00	13.2
Dust2	16	50%	1.01	14.1

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.

15.0%Headshot accuracy

33.1%Accuracy (enemy spotted)

36.0%Spray accuracy

81.1%Counter-strafing

8.5°Preaim

626msReaction time

42.5%T opening success

47.3%CT opening success

0.53Enemies flashed / flash

11.0%Flash assists

10.11HE damage / grenade

15.83Flashes / match

Recommended for you

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
cache	6–13	-0.04	19%	18 Aug →
ancient	13–5	0.00	9%	18 Aug →
ancient	13–1	-0.00	28%	18 Aug →
ancient	9–13	-0.00	14%	18 Aug →
nuke	11–13	0.04	8%	18 Aug →
nuke	13–2	-0.03	8%	16 Aug →
nuke	5–13	-0.04	12%	8 Aug →
cache	13–16	-0.05	12%	8 Aug →
nuke	13–16	-0.03	19%	8 Aug →
inferno	10–13	-0.01	14%	7 Aug →
ancient	1–4	-0.07	25%	7 Aug →
ancient	13–11	0.01	11%	7 Aug →
dust2	4–13	-0.02	10%	7 Aug →
ancient	12–8	0.01	9%	7 Aug →
mirage	6–13	0.04	17%	7 Aug →
ancient	13–7	0.09	9%	5 Aug →
mirage	9–13	-0.06	4%	4 Aug →
anubis	13–6	0.11	34%	4 Aug →
ancient	11–13	-0.02	16%	4 Aug →
dust2	8–13	-0.01	15%	4 Aug →
ancient	13–5	0.07	16%	2 Aug →
ancient	8–13	-0.03	8%	2 Aug →
ancient	13–11	-0.05	17%	2 Aug →
dust2	11–13	0.04	19%	2 Aug →
inferno	13–2	0.01	19%	2 Aug →
nuke	13–10	0.08	20%	1 Aug →
anubis	13–8	-0.02	11%	31 Jul →
ancient	13–10	0.03	17%	31 Jul →
anubis	4–13	-0.02	14%	31 Jul →
dust2	13–9	0.05	23%	30 Jul →
cache	13–1	0.07	8%	30 Jul →
ancient	0–13	-0.15	21%	30 Jul →
cache	13–9	0.08	21%	29 Jul →
nuke	3–13	-0.03	17%	29 Jul →
anubis	15–15	0.05	15%	28 Jul →
inferno	10–13	0.01	17%	27 Jul →
mirage	13–6	0.04	22%	27 Jul →
nuke	14–16	0.01	21%	26 Jul →
inferno	11–13	-0.00	10%	26 Jul →
nuke	13–11	-0.00	17%	26 Jul →
inferno	16–14	0.03	17%	26 Jul →
dust2	13–9	0.04	10%	26 Jul →
ancient	14–16	0.09	12%	26 Jul →
dust2	16–13	0.01	25%	26 Jul →
cache	12–16	-0.03	11%	24 Jul →
nuke	16–12	0.03	22%	24 Jul →
cache	13–5	0.11	30%	24 Jul →
anubis	13–6	-0.06	9%	23 Jul →
inferno	8–13	-0.08	8%	23 Jul →
nuke	10–13	-0.02	16%	23 Jul →
mirage	1–13	-0.07	8%	23 Jul →
anubis	13–10	0.12	20%	22 Jul →
ancient	13–9	-0.01	18%	21 Jul →
inferno	13–6	0.15	19%	20 Jul →
dust2	13–9	-0.01	31%	20 Jul →
anubis	13–10	-0.03	10%	17 Jul →
dust2	6–13	-0.01	28%	16 Jul →
anubis	13–5	0.06	17%	15 Jul →
dust2	13–7	-0.02	21%	15 Jul →
cache	6–13	0.04	25%	14 Jul →
inferno	13–3	-0.00	40%	14 Jul →
mirage	12–16	-0.02	16%	14 Jul →
anubis	13–11	-0.02	8%	13 Jul →
anubis	7–13	-0.03	11%	13 Jul →
dust2	4–13	0.09	24%	13 Jul →
ancient	8–13	-0.06	17%	12 Jul →
anubis	13–10	-0.01	13%	12 Jul →
ancient	10–13	0.01	14%	10 Jul →
cache	13–6	-0.05	11%	10 Jul →
anubis	7–13	-0.03	6%	10 Jul →
anubis	6–13	0.02	7%	10 Jul →
mirage	13–10	-0.00	12%	10 Jul →
ancient	6–13	-0.04	9%	10 Jul →
cache	13–5	0.08	14%	10 Jul →
cache	12–12	-0.02	16%	8 Jul →
cache	5–13	-0.02	21%	8 Jul →
cache	13–11	0.02	13%	7 Jul →
cache	13–11	0.04	7%	7 Jul →
nuke	9–5	-0.03	26%	7 Jul →
nuke	13–11	0.02	23%	5 Jul →
overpass	13–5	0.01	22%	5 Jul →
mirage	5–13	-0.03	26%	3 Jul →
inferno	5–9	0.06	10%	3 Jul →
nuke	13–8	-0.07	20%	2 Jul →
inferno	8–13	0.04	30%	2 Jul →
anubis	13–9	-0.01	19%	2 Jul →
nuke	13–10	-0.04	17%	1 Jul →
ancient	9–13	-0.05	4%	29 Jun →
anubis	15–15	0.06	23%	29 Jun →
inferno	7–13	0.01	21%	29 Jun →
inferno	9–13	-0.03	5%	28 Jun →
mirage	13–10	-0.04	6%	28 Jun →
nuke	7–13	0.05	22%	18 Jun →
ancient	8–13	-0.07	12%	18 Jun →
inferno	10–13	-0.05	27%	18 Jun →
mirage	10–13	-0.08	17%	13 Jun →
dust2	8–13	-0.07	26%	11 May →
anubis	15–15	-0.00	8%	8 May →
cache	13–5	0.07	17%	4 May →
cache	11–13	0.03	5%	4 May →