Loozty — CS2 Stats

76561198263702783[U:1:303437055]✓ No bans

3,262Tracked matches66%Win rate2020Tracked since

CSDB Rating7.4 StrongHybrid Rifler

Premier CS Rating26,597Top 25% of 819 CSDB-tracked playersRed band · top ~2.2% of ranked players (population est.)

Ladder ranks via Leetify

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Performance scores

Aim91

Positioning53

Utility61

0–100 skill scores via Leetify.

Recent form

STEADY62–36–2Last 10062%Win rateLWLLWLWLLW

Last 10 vs previous 10: -40pp win rate · -0.04 avg rating

Player DNA

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

Aim9.1

Aggression5.4

Utility6.1

Positioning5.3

Opening Duels2.4

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 NiKo 95% playstyle similarity

Most alike: utility contribution, 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

Aim. Aim score of 91 — the mechanical foundation is a clear strength.

Areas to improve

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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

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

Aim9.1

Positioning5.3

Utility6.1

Mechanics7.1

Opening Duels2.4

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 rating0.03−0.02

first ⅓ avg 0.05 → last ⅓ avg 0.03

Reaction time487ms−58ms

first ⅓ avg 545ms → last ⅓ avg 487ms

Headshot accuracy22.5%−1.1%

first ⅓ avg 23.6% → last ⅓ avg 22.5%

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.

Highlights

0.22Best rating — mirage 13–5

13–1Biggest win — inferno

10Longest win streak

7–6In matches decided by ≤2 rounds

5Overtime games

Map breakdown

dust2Best map · 80% over 10nukeWeakest map · 43% over 7

Map	Grade	Played	Record	Win rate	Avg rating
ancient	S	19	13–6	68%	0.04
mirage	S	17	13–4	76%	0.05
inferno	B	16	8–8	50%	0.03
vertigo	B	11	5–6	45%	0.03
dust2	S	10	8–2	80%	0.05
overpass	S	9	7–2	78%	0.07
nuke	C	7	3–4	43%	0.04
anubis	B	6	3–3	50%	0.03
cache	—	3	2–1	67%	0.05
cache_b	—	1	0–1	0%	0.07
tuscan_d	—	1	0–1	0%	-0.05

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (43% over 7). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

3,814Matches

53%Win rate

1.12Avg K/D

79.6ADR

52%Headshot %

Clutches & streaks

37%1v1 clutch win

25%1v2 clutch win

11Longest win streak

Recent Faceit resultsWLLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	367	54%	1.15	16.0
Mirage	218	56%	1.06	15.1
Anubis	203	47%	1.05	15.9
Nuke	117	56%	1.25	15.5
Vertigo	103	60%	1.30	16.2
Inferno	67	49%	1.23	17.0
Overpass	45	51%	1.28	16.3
Dust2	35	51%	0.94	12.8

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.

22.6%Headshot accuracy

38.4%Accuracy (enemy spotted)

41.7%Spray accuracy

82.1%Counter-strafing

8.4°Preaim

480msReaction time

32.6%T opening success

46.5%CT opening success

0.56Enemies flashed / flash

11.8%Flash assists

9.36HE damage / grenade

9.73Flashes / 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 32.621% — below the 40% mark we flag

Spend your practice time on Nuke

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

43% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
nuke	10–13	0.04	30%	23 Aug →
ancient	13–9	0.05	20%	23 Aug →
anubis	5–13	-0.01	15%	23 Aug →
dust2	6–13	-0.06	25%	22 Aug →
mirage	13–9	0.03	22%	22 Aug →
inferno	13–16	-0.06	30%	22 Aug →
ancient	13–11	0.03	15%	22 Aug →
ancient	8–13	-0.02	21%	21 Aug →
vertigo	8–13	0.02	26%	21 Aug →
mirage	13–11	-0.00	24%	17 Aug →
inferno	15–15	-0.06	13%	16 Aug →
vertigo	8–13	-0.02	29%	15 Aug →
cache	13–11	0.08	26%	15 Aug →
cache	9–1	0.09	35%	15 Aug →
overpass	13–9	0.07	33%	15 Aug →
ancient	13–10	0.02	30%	14 Aug →
dust2	13–6	0.13	18%	14 Aug →
vertigo	16–13	0.06	25%	14 Aug →
ancient	13–6	0.01	17%	12 Aug →
inferno	13–8	0.04	22%	6 Aug →
mirage	11–13	0.01	17%	5 Aug →
mirage	13–11	0.04	21%	4 Aug →
vertigo	13–2	0.11	18%	4 Aug →
cache	9–13	-0.02	35%	3 Aug →
inferno	13–1	0.16	22%	3 Aug →
ancient	0–13	-0.03	32%	26 Jul →
vertigo	13–7	0.04	9%	25 Jul →
vertigo	13–11	0.01	15%	24 Jul →
vertigo	13–8	0.06	24%	17 Jul →
ancient	13–10	0.03	19%	3 Jul →
ancient	13–1	0.06	13%	3 Jul →
inferno	13–10	-0.03	19%	17 Jun →
mirage	13–9	0.10	27%	13 Jun →
overpass	13–9	0.00	19%	6 Jun →
dust2	13–3	0.15	31%	6 Jun →
inferno	13–3	0.15	26%	6 Jun →
anubis	3–13	-0.04	26%	28 May →
anubis	12–12	0.01	22%	28 May →
dust2	13–5	0.06	43%	15 May →
mirage	13–11	-0.04	23%	13 May →
overpass	4–8	0.05	10%	13 May →
nuke	13–10	0.04	33%	10 May →
inferno	8–13	0.02	31%	9 May →
overpass	13–5	0.04	22%	9 May →
dust2	13–3	-0.01	18%	9 May →
mirage	13–7	0.00	31%	9 May →
ancient	13–1	0.10	37%	8 May →
inferno	9–13	0.04	22%	8 May →
ancient	13–2	0.13	12%	7 May →
inferno	6–13	0.01	16%	7 May →
ancient	8–13	0.06	25%	4 May →
dust2	13–5	0.03	33%	30 Apr →
ancient	3–13	0.04	26%	30 Apr →
nuke	4–13	0.00	33%	24 Apr →
dust2	13–9	0.04	30%	24 Apr →
ancient	13–7	0.01	47%	23 Apr →
inferno	6–13	-0.03	33%	23 Apr →
inferno	9–13	0.01	23%	21 Apr →
ancient	11–13	0.06	12%	18 Apr →
dust2	13–10	0.10	25%	15 Apr →
mirage	13–7	0.10	29%	15 Apr →
inferno	13–8	0.08	30%	15 Apr →
mirage	13–5	0.08	16%	14 Apr →
vertigo	8–13	0.02	16%	14 Apr →
inferno	13–7	0.02	24%	13 Apr →
anubis	13–11	0.00	21%	8 Apr →
vertigo	6–13	-0.03	28%	8 Apr →
vertigo	11–13	0.05	23%	6 Apr →
cache_b	8–13	0.07	17%	5 Apr →
tuscan_d	8–13	-0.05	29%	4 Apr →
dust2	11–13	0.02	31%	4 Apr →
ancient	13–8	-0.05	21%	3 Apr →
overpass	13–3	0.15	45%	3 Apr →
overpass	4–0	0.13	9%	1 Apr →
mirage	13–5	0.22	20%	1 Apr →
anubis	13–10	0.14	28%	1 Apr →
mirage	13–8	0.06	25%	29 Mar →
ancient	13–6	0.05	14%	21 Mar →
mirage	9–13	0.01	13%	18 Mar →
overpass	8–13	0.08	26%	12 Mar →
overpass	13–9	0.08	27%	12 Mar →
ancient	12–16	0.02	19%	9 Mar →
inferno	13–9	0.05	18%	9 Mar →
mirage	13–8	0.01	17%	1 Mar →
nuke	13–8	0.10	24%	1 Mar →
mirage	13–5	0.08	37%	27 Feb →
dust2	13–9	0.03	23%	27 Feb →
mirage	9–13	0.03	15%	27 Feb →
overpass	13–9	0.01	24%	24 Feb →
nuke	8–13	0.02	25%	24 Feb →
nuke	13–9	0.02	22%	24 Feb →
ancient	13–10	0.04	40%	22 Feb →
ancient	13–5	0.11	16%	22 Feb →
anubis	13–2	0.08	22%	22 Feb →
mirage	11–13	0.02	23%	21 Feb →
inferno	0–13	-0.07	19%	19 Feb →
vertigo	17–19	0.00	20%	19 Feb →
mirage	13–7	0.03	27%	18 Feb →
inferno	13–2	0.14	40%	15 Feb →
nuke	9–13	0.08	22%	15 Feb →