Aleeex — CS2 Stats

NO76561197988916298[U:1:28650570]Steam profile ↗✓ No bans

2,399Tracked matches45%Win rate2020Tracked since

CSDB Rating6.1 SolidAggressive Rifler

FaceitLevel 10 · 2,470 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim70

Positioning67

Utility71

0–100 skill scores via Leetify.

Recent form

STEADY50–47–3Last 10050%Win rateWWLWTLLLWL

Last 10 vs previous 10: +0pp win rate · +0.01 avg rating

Player DNA

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

Aim7.0

Aggression10.0

Utility7.1

Positioning6.7

Opening Duels4.4

Clutch3.8

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 ZywOo 92% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

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

Strengths

CT openings. 61% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

T-side openings. Opening success drops from 61% on CT to 35% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 615ms 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

Aim7.0

Positioning6.7

Utility7.1

Mechanics5.6

Opening Duels4.4

Win Impact3.3

Composite 6.1/10 (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+0.01

first ⅓ avg 0.02 → last ⅓ avg 0.03

Reaction time620ms−32ms

first ⅓ avg 652ms → last ⅓ avg 620ms

Headshot accuracy16.5%+0.4%

first ⅓ avg 16.1% → last ⅓ avg 16.5%

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

0.19Best rating — mirage 13–1

13–1Biggest win — cache

4Longest win streak

W2Current streak

6–14In matches decided by ≤2 rounds

10Overtime games

Map breakdown

infernoBest map · 76% over 21mirageWeakest map · 35% over 17

Map	Grade	Played	Record	Win rate	Avg rating
inferno	S	21	16–5	76%	0.03
ancient	A	19	12–7	63%	0.02
mirage	C	17	6–11	35%	0.04
nuke	C	11	4–7	36%	0.01
dust2	C	11	4–7	36%	0.02
cache	C	9	4–5	44%	0.02
overpass	C	7	3–4	43%	0.00
anubis	—	2	1–1	50%	0.06
train	—	2	0–2	0%	0.03
vertigo	—	1	0–1	0%	0.07

Across the last 100 tracked matches.

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

Faceit stats

Combat

2,568Matches

52%Win rate

1.37Avg K/D

97.1ADR

41%Headshot %

Clutches & streaks

39%1v1 clutch win

24%1v2 clutch win

11Longest win streak

Recent Faceit resultsLWLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	243	61%	1.50	21.0
Mirage	231	44%	1.38	20.8
Ancient	208	50%	1.38	20.0
Nuke	175	53%	1.50	20.3
Dust2	127	44%	1.29	19.5
Overpass	77	60%	1.48	19.0
Anubis	54	41%	1.18	17.2
Cache	23	74%	1.57	20.4

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.

16.1%Headshot accuracy

38.0%Accuracy (enemy spotted)

42.2%Spray accuracy

75.2%Counter-strafing

9.9°Preaim

615msReaction time

34.9%T opening success

60.7%CT opening success

0.69Enemies flashed / flash

15.7%Flash assists

10.13HE damage / grenade

7.44Flashes / 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 34.901% — below the 40% mark we flag

Spend your practice time on Mirage

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.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
ancient	13–5	0.01	18%	28 Aug →
cache	13–2	0.11	13%	28 Aug →
vertigo	9–13	0.07	12%	28 Aug →
ancient	13–7	0.10	17%	25 Aug →
cache	15–15	0.05	14%	25 Aug →
nuke	8–13	-0.00	27%	23 Aug →
cache	14–16	-0.02	12%	10 Aug →
inferno	6–13	0.01	25%	4 Aug →
ancient	13–5	0.07	17%	4 Aug →
cache	8–13	-0.01	18%	2 Aug →
nuke	13–9	0.03	18%	31 Jul →
cache	13–1	0.05	16%	31 Jul →
nuke	7–13	0.02	26%	28 Jul →
inferno	13–6	0.01	14%	28 Jul →
dust2	5–13	0.01	21%	28 Jul →
dust2	7–13	-0.06	12%	27 Jul →
dust2	11–13	0.06	20%	17 Jul →
inferno	11–13	0.00	13%	16 Jul →
mirage	8–13	0.06	8%	16 Jul →
inferno	13–10	0.07	13%	16 Jul →
ancient	11–13	0.05	21%	16 Jul →
dust2	13–2	0.08	22%	16 Jul →
inferno	13–7	0.04	12%	15 Jul →
nuke	13–10	0.06	21%	15 Jul →
ancient	13–10	0.02	20%	7 Jul →
mirage	7–13	-0.06	9%	7 Jul →
ancient	14–16	-0.00	11%	3 Jul →
inferno	9–13	0.01	11%	3 Jul →
cache	13–10	0.08	15%	2 Jul →
overpass	8–13	0.00	10%	8 Jun →
inferno	13–11	0.01	19%	5 Jun →
cache	11–13	0.00	15%	2 Jun →
ancient	10–13	0.02	24%	29 May →
inferno	13–5	0.00	20%	29 May →
cache	13–8	-0.02	14%	26 May →
nuke	5–13	-0.03	21%	26 May →
ancient	16–13	-0.01	10%	18 May →
dust2	10–13	0.05	35%	10 May →
cache	12–12	-0.02	19%	2 May →
ancient	7–13	-0.05	12%	2 May →
ancient	4–13	0.04	10%	1 May →
mirage	13–5	0.04	16%	30 Apr →
mirage	13–7	0.04	11%	22 Apr →
inferno	13–8	0.00	14%	10 Apr →
anubis	8–13	0.11	24%	10 Apr →
ancient	9–13	-0.05	20%	10 Apr →
mirage	13–9	0.09	18%	31 Mar →
nuke	13–9	0.02	24%	19 Mar →
ancient	13–4	0.01	25%	19 Mar →
inferno	15–15	0.01	18%	13 Mar →
mirage	11–13	0.01	16%	13 Mar →
dust2	5–13	-0.00	16%	13 Mar →
mirage	13–11	0.14	24%	12 Mar →
inferno	13–9	0.01	22%	12 Mar →
inferno	14–16	-0.01	13%	6 Mar →
inferno	13–8	0.00	15%	5 Mar →
inferno	13–10	0.03	24%	1 Mar →
mirage	13–1	0.19	18%	1 Mar →
ancient	13–5	0.02	10%	1 Mar →
nuke	11–13	0.02	19%	1 Mar →
overpass	13–8	0.00	15%	26 Feb →
nuke	13–3	-0.03	17%	25 Feb →
overpass	16–14	0.01	10%	25 Feb →
dust2	11–13	0.05	25%	24 Feb →
anubis	13–9	0.02	21%	24 Feb →
mirage	7–13	-0.02	14%	24 Feb →
inferno	13–5	0.10	22%	24 Feb →
mirage	11–13	0.01	24%	23 Feb →
inferno	13–9	0.01	13%	30 Jan →
dust2	13–8	0.05	22%	27 Jan →
mirage	9–13	-0.01	16%	27 Jan →
dust2	13–8	-0.01	24%	26 Jan →
ancient	13–9	-0.04	25%	24 Jan →
overpass	11–13	-0.05	18%	23 Jan →
nuke	6–13	-0.02	25%	23 Jan →
dust2	13–11	-0.01	19%	23 Jan →
mirage	11–13	0.06	14%	17 Jan →
ancient	13–9	0.07	17%	12 Jan →
ancient	13–10	0.06	16%	12 Jan →
inferno	13–7	0.04	15%	11 Jan →
overpass	7–13	-0.00	27%	10 Jan →
nuke	9–13	-0.02	15%	9 Jan →
dust2	6–13	0.01	15%	7 Jan →
inferno	13–5	0.04	13%	2 Jan →
mirage	13–8	0.03	16%	1 Jan →
inferno	13–9	0.06	18%	29 Dec →
mirage	6–13	0.03	20%	28 Dec →
mirage	4–13	0.02	19%	24 Dec →
train	11–13	0.07	23%	24 Dec →
nuke	16–19	0.03	16%	22 Dec →
ancient	2–13	-0.02	2%	19 Dec →
inferno	19–17	0.07	8%	17 Dec →
mirage	5–13	0.01	17%	3 Dec →
ancient	13–9	0.02	7%	3 Dec →
overpass	13–6	0.02	13%	3 Dec →
inferno	13–11	0.01	8%	3 Dec →
overpass	7–13	0.04	15%	28 Nov →
train	13–16	0.00	15%	27 Nov →
ancient	13–10	0.05	10%	27 Nov →
mirage	8–13	0.03	7%	27 Nov →