jollz — CS2 Stats

SE76561198014189253[U:1:53923525]Steam profile ↗✓ No bans

3,636Tracked matches63%Win rate2020Tracked since

CSDB Rating6.8 SolidAggressive Rifler

CSDB Leaderboard#4552 of 5231 tracked

FaceitLevel 10 · 2,714 ELOTop 12.4% of ranked FACEIT players

WingmanSupreme Master First Class

Ladder ranks via Leetify

Rating over time

2,714Peak Faceit ELO on CSDB

1Days observed since 2026-08-28

Faceit ELO

At peak — 2,714
Next: 3,000 ELO at 3,000 — 286 to go
Reached: 2,500 ELO · Level 10 · Level 9 · Level 8
2,500 ELO first seen 2026-08-28
Level 10 first seen 2026-08-28

CSDB's own observations — this history builds from the day a profile is first viewed and cannot be backfilled.

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Performance scores

Aim76

Positioning51

Utility74

0–100 skill scores via Leetify.

Recent form

STEADY53–47Last 10053%Win rateWWWLLLWLWW

Last 10 vs previous 10: -20pp win rate · -0.03 avg rating

Player DNA

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

Aim7.6

Aggression7.4

Utility7.4

Positioning5.1

Opening Duels3.1

Clutch3.4

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 Twistzz 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

Areas to improve

Reaction time. 605ms 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

Aim7.6

Positioning5.1

Utility7.4

Mechanics6.9

Opening Duels3.1

Win Impact9.4

Composite 6.8/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02−0.00

first ⅓ avg 0.03 → last ⅓ avg 0.02

Reaction time613ms+16ms

first ⅓ avg 597ms → last ⅓ avg 613ms

Headshot accuracy23.2%+2.6%

first ⅓ avg 20.6% → last ⅓ avg 23.2%

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

0.20Best rating — inferno 9–4

13–2Biggest win — dust2

7Longest win streak

W3Current streak

9–8In matches decided by ≤2 rounds

11Overtime games

Map breakdown

dust2Best map · 71% over 24cacheWeakest map · 18% over 11

Map	Grade	Played	Record	Win rate	Avg rating
dust2	S	24	17–7	71%	0.03
inferno	S	15	10–5	67%	0.05
anubis	A	15	9–6	60%	-0.00
ancient	B	14	7–7	50%	0.01
cache	D	11	2–9	18%	0.00
nuke	C	8	3–5	38%	0.02
mirage	D	6	2–4	33%	-0.03
overpass	—	4	2–2	50%	0.03
train	—	2	1–1	50%	-0.00
warden	—	1	0–1	0%	0.02

Across the last 100 tracked matches.

Faceit stats

Combat

2,890Matches

52%Win rate

1.08Avg K/D

77.5ADR

48%Headshot %

Clutches & streaks

37%1v1 clutch win

21%1v2 clutch win

12Longest win streak

Recent Faceit resultsWWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	409	50%	1.05	15.2
Ancient	389	56%	1.11	15.7
Inferno	378	53%	1.10	16.1
Anubis	369	55%	1.06	15.5
Mirage	247	46%	1.03	14.7
Nuke	211	47%	1.02	15.6
Vertigo	89	52%	1.06	14.7
Overpass	83	54%	1.09	15.5

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.

23.5%Headshot accuracy

35.2%Accuracy (enemy spotted)

34.7%Spray accuracy

81.0%Counter-strafing

9.2°Preaim

605msReaction time

37.9%T opening success

46.7%CT opening success

0.66Enemies flashed / flash

8.7%Flash assists

12.76HE damage / grenade

11.65Flashes / 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 37.9073% — below the 40% mark we flag

Spend your practice time on Cache

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

18% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
inferno	13–6	-0.01	38%	4 Aug →
anubis	13–6	-0.04	21%	4 Aug →
dust2	13–11	0.02	23%	3 Aug →
ancient	9–13	0.01	19%	29 Jun →
dust2	1–13	-0.05	21%	29 Jun →
nuke	13–16	-0.05	23%	29 Jun →
dust2	13–2	0.10	30%	25 Jun →
cache	4–13	0.04	16%	25 Jun →
cache	13–4	0.11	23%	24 Jun →
inferno	13–8	-0.01	34%	23 Jun →
nuke	13–6	0.01	10%	23 Jun →
ancient	13–8	0.01	13%	23 Jun →
dust2	13–9	-0.00	33%	23 Jun →
dust2	13–5	-0.02	8%	23 Jun →
dust2	13–5	0.03	35%	23 Jun →
dust2	10–13	0.10	32%	22 Jun →
overpass	13–5	0.11	32%	22 Jun →
anubis	13–10	0.05	31%	22 Jun →
ancient	4–13	0.01	14%	22 Jun →
dust2	13–3	0.12	38%	22 Jun →
anubis	13–10	0.01	18%	22 Jun →
warden	6–13	0.02	17%	22 Jun →
dust2	10–13	0.06	24%	21 Jun →
inferno	6–13	0.04	33%	21 Jun →
nuke	13–10	0.03	19%	21 Jun →
overpass	13–6	0.03	21%	21 Jun →
dust2	11–6	0.01	20%	21 Jun →
ancient	10–13	-0.04	15%	21 Jun →
dust2	19–17	0.01	25%	17 Jun →
ancient	7–13	-0.01	16%	17 Jun →
anubis	9–13	-0.06	13%	16 Jun →
inferno	13–11	0.11	20%	15 Jun →
dust2	11–13	0.06	28%	15 Jun →
nuke	11–13	0.03	15%	14 Jun →
mirage	2–13	-0.03	22%	14 Jun →
anubis	13–6	0.01	12%	14 Jun →
mirage	3–13	-0.00	41%	12 Jun →
anubis	8–13	-0.07	13%	12 Jun →
inferno	13–11	0.03	30%	12 Jun →
dust2	13–11	0.11	32%	12 Jun →
nuke	12–16	0.02	20%	11 Jun →
ancient	10–13	-0.04	27%	11 Jun →
mirage	13–9	-0.04	19%	10 Jun →
ancient	13–10	-0.02	19%	10 Jun →
dust2	16–13	0.01	33%	10 Jun →
anubis	13–8	0.02	26%	10 Jun →
nuke	13–4	0.08	29%	9 Jun →
ancient	16–12	0.02	14%	9 Jun →
cache	5–13	0.06	20%	9 Jun →
cache	5–13	-0.02	15%	5 Jun →
nuke	9–13	-0.05	6%	5 Jun →
anubis	13–10	0.01	17%	5 Jun →
mirage	3–13	-0.08	9%	5 Jun →
cache	7–13	-0.08	23%	4 Jun →
dust2	13–7	0.03	18%	4 Jun →
overpass	5–13	-0.07	8%	4 Jun →
dust2	11–13	0.02	32%	3 Jun →
ancient	13–10	0.01	13%	3 Jun →
inferno	13–5	0.01	20%	3 Jun →
inferno	16–14	0.06	33%	3 Jun →
anubis	4–13	-0.10	14%	21 May →
dust2	5–13	0.02	23%	20 May →
anubis	13–10	0.04	38%	19 May →
cache	6–13	-0.07	3%	9 May →
dust2	13–9	-0.02	18%	9 May →
cache	6–13	-0.03	20%	9 May →
inferno	13–11	0.03	33%	6 May →
cache	17–19	-0.02	20%	4 May →
anubis	13–9	0.01	23%	4 May →
ancient	13–11	0.03	12%	4 May →
cache	13–6	0.03	25%	3 May →
cache	6–13	-0.00	42%	30 Apr →
cache	17–19	0.03	17%	29 Apr →
ancient	6–13	0.08	17%	29 Apr →
mirage	11–13	0.02	21%	28 Apr →
dust2	13–10	0.03	20%	28 Apr →
ancient	13–4	0.03	15%	27 Apr →
overpass	8–13	0.04	16%	27 Apr →
inferno	8–13	-0.05	11%	25 Apr →
inferno	13–16	0.02	13%	25 Apr →
dust2	13–7	-0.06	17%	25 Apr →
nuke	10–13	0.05	28%	24 Apr →
dust2	13–10	0.00	21%	24 Apr →
mirage	13–7	-0.02	27%	24 Apr →
inferno	17–19	0.05	19%	23 Apr →
train	2–13	-0.03	31%	23 Apr →
ancient	8–13	0.08	19%	23 Apr →
inferno	13–10	0.13	19%	23 Apr →
ancient	13–9	-0.00	31%	23 Apr →
dust2	13–7	0.04	16%	23 Apr →
train	8–1	0.02	13%	23 Apr →
anubis	10–13	0.02	13%	23 Apr →
inferno	5–13	0.07	23%	22 Apr →
anubis	3–13	-0.03	19%	22 Apr →
anubis	9–13	0.02	26%	22 Apr →
dust2	11–13	-0.02	18%	21 Apr →
anubis	19–17	0.06	26%	21 Apr →
dust2	13–8	0.08	21%	21 Apr →
inferno	13–8	0.02	24%	21 Apr →
inferno	9–4	0.20	18%	21 Apr →