Bello-_- — CS2 Stats

76561198207905304[U:1:247639576]✓ No bans

405Tracked matches55%Win rate2020Tracked since

CSDB Rating5.7 SolidHybrid Rifler

FaceitLevel 8Top 31.2% of ranked FACEIT players

WingmanDistinguished Master Guardian

Ladder ranks via Leetify

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Performance scores

Aim79

Positioning41

Utility42

0–100 skill scores via Leetify.

Recent form

STEADY50–47–3Last 10050%Win rateLLWWWTWTLL

Last 10 vs previous 10: -40pp win rate · -0.02 avg rating

Player DNA

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

Aim7.9

Aggression4.9

Utility4.2

Positioning4.1

Opening Duels0.5

Clutch1.0

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 83% playstyle similarity

Most alike: opening-fight frequency, aim profile.

Where you differ: lower utility contribution; lower opening-duel success.

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

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.

Reaction time. 602ms 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

Aim7.9

Positioning4.1

Utility4.2

Mechanics7.4

Opening Duels0.8

Win Impact6.7

Composite 5.7/10 (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 rating-0.01+0.01

first ⅓ avg -0.02 → last ⅓ avg -0.01

Reaction time608ms−8ms

first ⅓ avg 616ms → last ⅓ avg 608ms

Headshot accuracy26.5%+1.4%

first ⅓ avg 25.1% → last ⅓ avg 26.5%

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

0.10Best rating — inferno 13–8

13–1Biggest win — anubis

6Longest win streak

L2Current streak

8–10In matches decided by ≤2 rounds

9Overtime games

Map breakdown

anubisBest map · 57% over 7trainWeakest map · 38% over 8

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	22	10–12	45%	-0.01
nuke	B	17	9–8	53%	-0.00
inferno	B	15	7–8	47%	-0.02
ancient	C	10	4–6	40%	-0.02
train	C	8	3–5	38%	0.02
anubis	A	7	4–3	57%	0.00
dust2	C	7	3–4	43%	-0.02
overpass	C	5	2–3	40%	-0.00
cache	—	4	4–0	100%	0.01
vertigo	—	4	4–0	100%	0.01
golden	—	1	0–1	0%	-0.06

Across the last 100 tracked matches.

Faceit stats

Combat

499Matches

55%Win rate

1.00Avg K/D

73.1ADR

45%Headshot %

Clutches & streaks

25%1v1 clutch win

6%1v2 clutch win

7Longest win streak

Recent Faceit resultsWLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	9	67%	1.05	15.6
Cache	4	75%	1.31	15.5
Dust2	3	67%	0.83	15.3
Nuke	3	33%	1.06	17.0
Vertigo	3	33%	0.75	12.0
Ancient	1	100%	0.47	7.0
Anubis	1	100%	0.53	10.0

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.

26.9%Headshot accuracy

32.0%Accuracy (enemy spotted)

36.6%Spray accuracy

83.3%Counter-strafing

9.1°Preaim

602msReaction time

27.8%T opening success

36.4%CT opening success

0.44Enemies flashed / flash

3.8%Flash assists

8.88HE damage / grenade

6.09Flashes / 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 0.4369 — 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 27.7942% — below the 40% mark we flag

Spend your practice time on Train

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

38% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
mirage	12–16	-0.08	30%	27 Aug →
nuke	11–13	-0.03	28%	27 Aug →
mirage	13–4	0.05	13%	22 Aug →
cache	13–8	0.07	38%	5 Aug →
mirage	13–8	-0.05	21%	5 Aug →
mirage	15–15	-0.01	20%	18 Jul →
inferno	13–11	-0.02	22%	18 Jul →
inferno	8–8	-0.01	32%	15 Jul →
mirage	7–13	-0.07	55%	15 Jul →
mirage	6–13	-0.08	26%	15 Jul →
cache	13–6	0.00	23%	15 Jul →
nuke	16–13	-0.00	20%	14 Jul →
inferno	9–13	-0.01	36%	14 Jul →
mirage	13–7	-0.05	21%	14 Jul →
nuke	13–9	-0.05	35%	13 Jul →
mirage	13–6	0.01	31%	13 Jul →
cache	13–8	-0.02	17%	9 Jul →
mirage	3–13	-0.03	21%	9 Jul →
inferno	13–11	0.00	28%	21 May →
anubis	13–1	0.08	24%	21 May →
mirage	7–13	0.02	24%	21 May →
cache	13–11	0.00	41%	21 May →
ancient	7–13	-0.04	29%	23 Apr →
anubis	13–9	-0.02	18%	20 Apr →
nuke	4–13	0.02	23%	20 Apr →
mirage	9–13	-0.00	23%	9 Mar →
train	11–13	0.05	44%	4 Jan →
mirage	14–16	-0.00	28%	3 Jan →
inferno	11–13	0.01	22%	3 Jan →
train	13–7	0.02	15%	3 Jan →
mirage	13–3	0.05	27%	3 Jan →
ancient	11–13	-0.02	27%	3 Jan →
overpass	14–16	-0.00	11%	3 Jan →
nuke	13–8	0.09	43%	3 Jan →
golden	6–13	-0.06	27%	3 Jan →
vertigo	13–8	0.07	22%	3 Jan →
overpass	7–13	-0.01	27%	3 Jan →
ancient	5–13	-0.06	18%	3 Jan →
dust2	9–13	-0.04	24%	2 Jan →
inferno	10–13	-0.04	21%	2 Jan →
nuke	11–13	0.01	25%	2 Jan →
nuke	13–10	0.07	28%	2 Jan →
inferno	13–8	0.10	20%	2 Jan →
mirage	11–13	0.08	28%	2 Jan →
ancient	13–9	-0.04	21%	30 Dec →
mirage	13–9	0.08	17%	30 Dec →
nuke	7–13	-0.05	23%	30 Dec →
inferno	4–13	-0.04	55%	30 Dec →
mirage	5–13	-0.00	26%	30 Dec →
train	6–13	-0.04	22%	30 Dec →
inferno	13–7	-0.01	19%	28 Dec →
overpass	13–7	0.02	17%	28 Dec →
nuke	10–13	-0.04	30%	27 Dec →
ancient	10–13	-0.00	21%	27 Dec →
inferno	6–13	0.03	22%	23 Dec →
dust2	4–13	-0.05	30%	28 Nov →
mirage	13–11	-0.00	34%	28 Nov →
anubis	9–13	0.01	39%	21 Nov →
overpass	9–13	-0.03	28%	21 Nov →
vertigo	13–6	0.02	33%	1 May →
mirage	13–3	0.06	28%	1 May →
vertigo	13–8	0.01	20%	11 Apr →
train	3–13	0.00	19%	11 Apr →
ancient	13–8	0.03	36%	11 Apr →
nuke	13–8	0.03	25%	11 Apr →
anubis	12–12	-0.01	37%	11 Apr →
train	13–3	0.09	26%	11 Apr →
vertigo	13–5	-0.04	37%	9 Apr →
ancient	13–1	-0.01	21%	9 Apr →
train	8–13	0.01	31%	9 Apr →
nuke	13–11	-0.01	30%	9 Apr →
overpass	13–9	0.02	29%	9 Apr →
inferno	13–11	-0.07	15%	7 Apr →
dust2	16–13	-0.00	26%	27 Mar →
anubis	13–2	-0.03	21%	27 Mar →
nuke	13–3	0.05	27%	27 Mar →
nuke	7–13	-0.07	38%	26 Mar →
train	5–13	-0.03	36%	26 Mar →
nuke	13–7	0.03	26%	26 Mar →
anubis	14–16	-0.04	24%	19 Mar →
nuke	11–13	-0.06	15%	19 Mar →
anubis	13–9	0.03	31%	19 Mar →
nuke	2–13	-0.04	29%	19 Mar →
dust2	13–2	0.00	26%	9 Mar →
ancient	8–13	0.00	31%	9 Mar →
train	13–6	0.05	34%	9 Mar →
dust2	7–13	-0.03	35%	9 Mar →
inferno	16–13	-0.03	21%	6 Mar →
inferno	4–13	-0.06	31%	6 Mar →
mirage	13–6	-0.04	24%	6 Mar →
inferno	6–13	-0.06	23%	5 Mar →
mirage	9–13	-0.01	24%	5 Mar →
ancient	13–9	-0.01	16%	5 Mar →
mirage	13–4	-0.06	18%	5 Mar →
nuke	13–11	0.03	21%	5 Mar →
ancient	4–13	-0.04	9%	4 Mar →
mirage	9–13	0.02	21%	4 Mar →
inferno	16–12	-0.04	23%	2 Mar →
dust2	9–13	-0.05	36%	2 Mar →
dust2	2–0	0.00	0%	2 Mar →