ph1L- — CS2 Stats

76561198157876304[U:1:197610576]

2,803Tracked matches54%Win rate2020Tracked since

CSDB Rating6.1 SolidHybrid Rifler

FaceitLevel 10 · 2,379 ELOTop 12.4% of ranked FACEIT players

WingmanLegendary Eagle Master

Ladder ranks via Leetify

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Performance scores

Aim64

Positioning66

Utility70

0–100 skill scores via Leetify.

Recent form

STEADY46–49–5Last 10046%Win rateLWWWTWWLLW

Last 10 vs previous 10: +10pp win rate · +0.03 avg rating

Player DNA

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

Aim6.4

Aggression8.4

Utility7.0

Positioning6.6

Opening Duels4.7

Clutch4.4

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: 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

Strengths

CT openings. 65% 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 65% on CT to 33% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 623ms 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

Positioning6.6

Utility7.0

Mechanics5.0

Opening Duels4.7

Win Impact6.2

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 rating0.01−0.03

first ⅓ avg 0.04 → last ⅓ avg 0.01

Reaction time627ms+10ms

first ⅓ avg 618ms → last ⅓ avg 627ms

Headshot accuracy23.6%+0.3%

first ⅓ avg 23.3% → last ⅓ avg 23.6%

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

0.18Best rating — nuke 13–4

13–1Biggest win — vertigo

3Longest win streak

6–10In matches decided by ≤2 rounds

15Overtime games

Map breakdown

vertigoBest map · 57% over 7infernoWeakest map · 29% over 7

Map	Grade	Played	Record	Win rate	Avg rating
ancient	B	23	11–12	48%	0.02
overpass	B	17	9–8	53%	0.02
nuke	B	14	7–7	50%	0.07
mirage	D	9	3–6	33%	0.04
cache	B	8	4–4	50%	-0.03
anubis	C	8	3–5	38%	-0.00
vertigo	A	7	4–3	57%	0.00
inferno	D	7	2–5	29%	-0.01
dust2	—	2	2–0	100%	0.09
fachwerk	—	1	0–1	0%	0.03
warden	—	1	0–1	0%	-0.04
stronghold	—	1	1–0	100%	0.08
train	—	1	0–1	0%	-0.03
rooftop	—	1	0–1	0%	0.02

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,882Matches

51%Win rate

1.17Avg K/D

86.3ADR

52%Headshot %

Clutches & streaks

42%1v1 clutch win

26%1v2 clutch win

11Longest win streak

Recent Faceit resultsLWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	265	53%	1.22	18.1
Anubis	197	49%	1.16	18.0
Mirage	168	42%	1.05	17.0
Nuke	161	47%	1.21	18.5
Vertigo	113	56%	1.23	18.4
Inferno	100	55%	1.20	18.0
Overpass	100	60%	1.26	19.2
Train	52	42%	1.13	17.8

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.

22.8%Headshot accuracy

37.8%Accuracy (enemy spotted)

38.0%Spray accuracy

72.3%Counter-strafing

12.7°Preaim

623msReaction time

33.0%T opening success

64.8%CT opening success

0.56Enemies flashed / flash

11.1%Flash assists

11.63HE damage / grenade

9.93Flashes / 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
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 12.7162° — above the 12° mark we flag
Aim Training →

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.

29% win rate across 7 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	7–13	-0.02	31%	20 Aug →
vertigo	16–13	-0.03	17%	18 Aug →
vertigo	16–13	0.08	25%	13 Aug →
ancient	13–11	-0.02	16%	13 Aug →
fachwerk	12–12	0.03	31%	11 Aug →
ancient	13–10	-0.04	20%	3 Aug →
vertigo	13–8	0.00	23%	3 Aug →
ancient	7–13	0.08	27%	25 Jul →
mirage	6–13	0.11	24%	25 Jul →
anubis	13–8	0.09	27%	25 Jul →
ancient	15–15	0.09	20%	25 Jul →
inferno	13–7	0.01	25%	14 Jul →
cache	8–13	-0.07	22%	14 Jul →
anubis	7–13	-0.02	25%	9 Jul →
ancient	13–11	0.02	25%	9 Jul →
inferno	13–10	0.05	26%	5 Jul →
ancient	10–13	-0.07	10%	1 Jul →
overpass	13–3	0.02	27%	1 Jul →
anubis	13–8	-0.00	23%	1 Jul →
inferno	8–13	-0.04	17%	17 Jun →
mirage	11–13	0.04	29%	17 Jun →
overpass	13–16	-0.00	21%	17 Jun →
ancient	9–13	-0.04	23%	9 Jun →
nuke	16–12	-0.01	39%	9 Jun →
nuke	13–10	0.05	23%	5 Jun →
inferno	11–13	-0.03	18%	5 Jun →
ancient	11–13	0.02	15%	5 Jun →
anubis	13–7	-0.04	22%	3 Jun →
overpass	13–7	0.06	14%	31 May →
mirage	10–13	-0.04	17%	29 May →
cache	1–4	-0.12	50%	29 May →
anubis	13–16	0.00	27%	29 May →
nuke	13–4	0.03	18%	27 May →
nuke	13–16	0.01	25%	26 May →
overpass	10–13	0.02	16%	25 May →
vertigo	13–1	0.05	21%	25 May →
cache	9–13	-0.01	22%	13 May →
nuke	13–6	0.11	26%	12 May →
anubis	10–13	0.00	21%	12 May →
ancient	15–15	-0.01	12%	12 May →
overpass	2–13	-0.12	14%	12 May →
ancient	13–10	0.03	18%	12 May →
cache	13–1	0.03	31%	10 May →
ancient	13–11	0.02	24%	10 May →
ancient	10–13	0.06	32%	7 May →
ancient	13–9	0.01	27%	6 May →
cache	13–7	-0.01	23%	6 May →
inferno	8–13	0.01	33%	4 May →
cache	13–10	-0.05	30%	29 Apr →
cache	13–9	-0.01	16%	28 Apr →
warden	0–9	-0.04	0%	23 Apr →
vertigo	2–13	-0.07	19%	23 Apr →
overpass	13–8	0.02	18%	13 Apr →
stronghold	13–9	0.08	16%	11 Apr →
vertigo	12–12	0.00	21%	11 Apr →
ancient	13–11	0.13	25%	5 Apr →
dust2	16–14	0.07	20%	5 Apr →
mirage	5–13	0.04	30%	5 Apr →
dust2	13–2	0.11	36%	5 Apr →
overpass	3–13	0.00	34%	5 Apr →
ancient	8–13	0.08	18%	5 Apr →
overpass	13–5	0.01	20%	29 Mar →
nuke	11–13	0.17	24%	29 Mar →
mirage	13–7	0.05	16%	28 Mar →
nuke	5–13	-0.01	17%	27 Mar →
overpass	25–22	0.01	20%	26 Mar →
ancient	6–13	-0.05	10%	26 Mar →
ancient	8–13	0.08	27%	25 Mar →
overpass	17–19	-0.02	18%	19 Mar →
nuke	13–3	0.14	29%	19 Mar →
inferno	8–13	-0.09	31%	18 Mar →
nuke	5–13	-0.05	24%	18 Mar →
vertigo	6–13	-0.01	22%	14 Mar →
overpass	11–13	0.05	24%	12 Mar →
nuke	13–4	0.18	33%	11 Mar →
mirage	13–7	0.09	27%	11 Mar →
anubis	11–13	0.00	21%	21 Feb →
overpass	6–13	-0.00	24%	11 Feb →
anubis	6–13	-0.05	22%	11 Feb →
ancient	13–5	0.05	18%	10 Feb →
nuke	16–13	0.06	22%	20 Jan →
nuke	16–19	0.06	20%	9 Jan →
mirage	13–8	0.10	19%	9 Jan →
ancient	13–8	0.06	24%	23 Dec →
overpass	13–10	0.04	32%	23 Dec →
overpass	11–13	0.10	22%	22 Dec →
nuke	14–16	0.12	18%	10 Dec →
ancient	13–6	0.09	28%	10 Dec →
mirage	6–13	-0.05	22%	10 Dec →
overpass	13–10	0.01	15%	9 Dec →
ancient	13–11	0.02	20%	9 Dec →
inferno	8–13	0.02	31%	3 Dec →
overpass	13–2	0.06	21%	3 Dec →
mirage	11–13	-0.02	16%	3 Dec →
overpass	13–10	0.11	25%	2 Dec →
nuke	12–16	0.08	30%	30 Nov →
train	5–13	-0.03	31%	28 Nov →
ancient	10–13	-0.02	16%	17 Nov →
ancient	9–13	-0.03	19%	11 Nov →
rooftop	8–8	0.02	19%	10 Nov →