JBella — CS2 Stats

US76561199524157968[U:1:1563892240]Steam profile ↗✓ No bans

2,683Tracked matches50%Win rate2023Tracked since

3,622Hours in CS2Hrs last 2 wks

CSDB Rating5.9 SolidAggressive Rifler

WingmanGold Nova Master

Ladder ranks via Leetify

Performance scores

Aim81

Positioning58

Utility28

0–100 skill scores via Leetify.

Recent form

STEADY39–47–14Last 10039%Win rateWWLWLLLWLL

Last 10 vs previous 10: +10pp win rate · +0.05 avg rating

Player DNA

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

Aim8.1

Aggression8.9

Utility2.8

Positioning5.8

Opening Duels3.6

Clutch0.0

Limited utility dependence

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 87% playstyle similarity

Most alike: opening-duel success, opening-fight frequency.

Where you differ: lower utility contribution.

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

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

Aim8.1

Positioning5.8

Utility2.8

Mechanics7.0

Opening Duels3.6

Win Impact5.0

Composite 5.9/10 (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 rating0.02+0.03

first ⅓ avg -0.01 → last ⅓ avg 0.02

Reaction time539ms−99ms

first ⅓ avg 638ms → last ⅓ avg 539ms

Headshot accuracy16.1%−0.1%

first ⅓ avg 16.2% → last ⅓ avg 16.1%

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

0.23Best rating — dust2 13–7

13–2Biggest win — vertigo

5Longest win streak

W2Current streak

5–10In matches decided by ≤2 rounds

1Overtime games

Map breakdown

nukeBest map · 50% over 8infernoWeakest map · 14% over 7

Map	Grade	Played	Record	Win rate	Avg rating
dust2	D	15	5–10	33%	0.04
vertigo	C	14	6–8	43%	0.04
cache	B	11	5–6	45%	0.02
office	C	9	4–5	44%	0.02
mirage	C	9	4–5	44%	-0.01
nuke	B	8	4–4	50%	-0.01
inferno	D	7	1–6	14%	-0.02
anubis	B	6	3–3	50%	0.01
italy	C	5	2–3	40%	0.02
shelter	—	4	1–3	25%	0.00
boulder	—	3	1–2	33%	0.01
fachwerk	—	2	1–1	50%	0.01
ancient	—	2	1–1	50%	0.08
alpine	—	2	0–2	0%	-0.01
overpass	—	1	0–1	0%	0.11
warden	—	1	1–0	100%	0.01
train	—	1	0–1	0%	-0.11

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (14% over 7). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

84,184Lifetime kills

1.26K/D · Top 25% of tracked players

5,497Matches

49.6%Match win rate · Top 25% of tracked players

31.7%Headshot %

2.3%Shot accuracy

10,671MVPs

1,858Hours (in match)

4,169Bombs planted

865Bombs defused

Most-used weapons

AWP24,202

AK-4719,389

M4A4 / M4A1-S18,716

P2000 / USP-S4,122

SSG 083,114

Desert Eagle2,380

Glock-182,060

P2501,453

Galil AR1,245

XM10141,152

Lifetime map wins

7,689dust2

6,444inferno

6,243nuke

4,209vertigo

1,893office

885train

777italy

48safehouse

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

6Matches

67%Win rate

0.98Avg K/D

78.8ADR

38%Headshot %

Clutches & streaks

0%1v1 clutch win

0%1v2 clutch win

4Longest win streak

Recent Faceit resultsWWWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	2	100%	0.99	16.5
Nuke	1	100%	0.84	16.0
Anubis	1	0%	0.79	11.0
Ancient	1	0%	0.61	11.0
Dust2	1	100%	1.67	15.0

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.

16.9%Headshot accuracy

37.7%Accuracy (enemy spotted)

33.9%Spray accuracy

81.3%Counter-strafing

7.6°Preaim

540msReaction time

38.8%T opening success

50.3%CT opening success

0.33Enemies flashed / flash

4.9%Flash assists

10.71HE damage / grenade

0.90Flashes / 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.

Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.3292 — below the 0.5 mark we flag
Grenade Lineups →
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 38.8043% — below the 40% mark we flag

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.

14% 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
office	13–6	0.05	24%	28 Aug →
dust2	13–7	-0.04	15%	17 Aug →
italy	9–13	0.09	11%	15 Aug →
office	13–6	0.12	17%	12 Aug →
dust2	9–13	0.03	32%	9 Aug →
shelter	9–13	0.06	24%	9 Aug →
dust2	8–13	0.07	23%	7 Aug →
vertigo	13–4	0.12	17%	30 Jul →
office	11–13	-0.05	20%	30 Jul →
office	6–13	-0.04	10%	26 Jul →
vertigo	7–13	-0.07	16%	23 Jul →
shelter	6–13	-0.02	13%	19 Jul →
shelter	8–13	-0.03	15%	18 Jul →
fachwerk	3–13	0.02	13%	16 Jul →
fachwerk	13–11	-0.00	16%	15 Jul →
boulder	12–12	-0.04	6%	15 Jul →
boulder	13–5	0.11	21%	12 Jul →
shelter	13–7	-0.01	18%	11 Jul →
boulder	12–12	-0.05	17%	11 Jul →
cache	12–12	0.04	20%	7 Jul →
ancient	12–12	0.06	27%	7 Jul →
vertigo	11–2	0.16	19%	3 Jul →
office	13–11	-0.01	21%	1 Jul →
office	13–7	0.02	16%	25 Jun →
dust2	8–3	0.00	11%	18 Jun →
office	12–12	0.07	16%	17 Jun →
cache	13–4	-0.02	14%	15 Jun →
cache	8–13	-0.05	0%	7 Jun →
office	12–12	-0.01	19%	7 Jun →
mirage	14–16	0.06	13%	31 May →
inferno	7–13	-0.05	17%	30 May →
anubis	12–12	-0.01	4%	28 May →
vertigo	13–4	0.05	9%	28 May →
dust2	13–7	0.23	23%	23 May →
cache	13–4	0.11	28%	23 May →
office	5–8	-0.01	12%	22 May →
cache	8–2	0.02	8%	22 May →
nuke	13–11	0.05	10%	20 May →
overpass	11–13	0.11	17%	20 May →
cache	1–13	-0.07	14%	19 May →
alpine	11–13	0.00	13%	19 May →
cache	12–12	0.03	21%	19 May →
anubis	13–6	-0.00	17%	16 May →
mirage	12–12	0.00	18%	16 May →
italy	6–10	0.03	25%	14 May →
mirage	13–9	0.00	14%	14 May →
cache	13–5	0.01	13%	14 May →
vertigo	9–13	-0.02	28%	14 May →
nuke	8–13	-0.00	22%	13 May →
dust2	11–13	0.11	24%	13 May →
anubis	1–13	-0.03	11%	13 May →
cache	13–5	0.10	20%	13 May →
cache	5–13	0.01	20%	13 May →
cache	11–13	0.03	21%	1 May →
nuke	13–5	0.06	7%	24 Apr →
vertigo	13–2	0.14	16%	17 Apr →
dust2	13–2	0.11	13%	17 Apr →
mirage	3–13	-0.00	21%	17 Apr →
mirage	13–8	-0.01	26%	15 Apr →
vertigo	13–3	0.09	14%	15 Apr →
ancient	13–2	0.10	14%	15 Apr →
nuke	13–7	0.06	14%	12 Apr →
warden	13–5	0.01	11%	10 Apr →
vertigo	11–13	-0.04	16%	10 Apr →
inferno	11–13	-0.01	26%	10 Apr →
dust2	7–13	-0.00	16%	5 Apr →
inferno	11–13	-0.00	6%	5 Apr →
italy	13–7	0.03	17%	4 Apr →
dust2	4–13	0.00	20%	4 Apr →
anubis	11–13	0.05	12%	3 Apr →
nuke	6–13	0.03	14%	3 Apr →
anubis	13–9	-0.03	15%	29 Mar →
mirage	4–13	-0.05	17%	29 Mar →
vertigo	4–13	-0.01	20%	27 Mar →
dust2	6–13	-0.08	7%	27 Mar →
italy	13–6	-0.02	26%	27 Mar →
mirage	4–13	-0.06	42%	27 Mar →
nuke	13–11	-0.07	15%	26 Mar →
anubis	13–8	0.08	19%	26 Mar →
italy	6–13	-0.03	9%	23 Mar →
vertigo	12–12	0.01	2%	23 Mar →
nuke	1–11	-0.12	27%	23 Mar →
vertigo	7–13	-0.01	15%	23 Mar →
dust2	12–12	-0.01	19%	22 Mar →
mirage	13–4	-0.03	30%	22 Mar →
inferno	3–13	0.03	9%	22 Mar →
inferno	13–8	0.01	8%	21 Mar →
dust2	12–12	0.04	6%	21 Mar →
nuke	10–13	-0.05	10%	21 Mar →
vertigo	13–10	0.02	18%	21 Mar →
vertigo	12–12	0.15	15%	20 Mar →
inferno	12–12	-0.03	14%	19 Mar →
vertigo	9–13	-0.04	13%	18 Mar →
mirage	13–11	-0.02	23%	18 Mar →
dust2	13–3	0.06	16%	18 Mar →
alpine	5–13	-0.01	12%	17 Mar →
dust2	10–13	0.09	21%	15 Mar →
train	1–8	-0.11	0%	14 Mar →
dust2	10–13	-0.05	29%	14 Mar →
inferno	0–13	-0.05	10%	14 Mar →