BING BONG — CS2 Stats

US76561198114912371[U:1:154646643]Steam profile ↗

1,345Tracked matches50%Win rate2020Tracked since

4,299Hours in CS57Hrs last 2 wks

CSDB Rating6.2 SolidAggressive Rifler

Premier CS Rating23,524Top 50% of 819 CSDB-tracked playersPink band · top ~4.6% of ranked players (population est.)

CSDB Leaderboard#3254 of 13236 tracked

FaceitLevel 8 · 1,782 ELOTop 31.2% of ranked FACEIT players

WingmanLegendary Eagle

Ladder ranks via Leetify

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Performance scores

Aim87

Positioning53

Utility31

0–100 skill scores via Leetify.

Recent form

STEADY50–46–4Last 10050%Win rateWLWLWLLLLW

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

Player DNA

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

Aim8.7

Aggression7.0

Utility3.1

Positioning5.3

Opening Duels2.6

Clutch5.2

Sharp aimerStrong CT-side openerLimited 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 ropz 88% playstyle similarity

Most alike: opening-fight frequency, positioning 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

Strengths

Aim. Aim score of 87 — the mechanical foundation is a clear strength.

Areas to improve

Positioning. Positioning trails aim by 34 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.

T-side openings. Opening success drops from 48% on CT to 33% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 567ms 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

Aim8.7

Positioning5.3

Utility3.1

Mechanics7.9

Opening Duels2.6

Win Impact5.0

Composite 6.2/10 (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+0.01

first ⅓ avg 0.01 → last ⅓ avg 0.02

Reaction time568ms−77ms

first ⅓ avg 645ms → last ⅓ avg 568ms

Headshot accuracy22.8%+0.0%

first ⅓ avg 22.7% → last ⅓ avg 22.8%

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

0.11Best rating — dust2 13–10

13–2Biggest win — mirage

5Longest win streak

6–9In matches decided by ≤2 rounds

8Overtime games

Map breakdown

nukeBest map · 60% over 15anubisWeakest map · 40% over 5

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	20	10–10	50%	0.01
dust2	A	20	11–9	55%	0.01
inferno	B	17	8–9	47%	0.01
nuke	A	15	9–6	60%	0.01
ancient	B	13	7–6	54%	0.02
cache	B	6	3–3	50%	0.00
anubis	C	5	2–3	40%	0.03
train	—	3	0–3	0%	-0.01
vertigo	—	1	0–1	0%	0.01

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (40% over 5). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

94,046Lifetime kills

1.23K/D · Top 50% of Pink band

4,425Matches

41.0%Match win rate

47.5%Headshot %

13.7%Shot accuracy · Top 50% of Pink band

10,535MVPs

1,636Hours (in match)

2,422Bombs planted

1,132Bombs defused

Most-used weapons

AK-4735,581

M4A4 / M4A1-S17,673

AWP7,854

Desert Eagle4,760

P2000 / USP-S4,335

Glock-183,421

P902,777

Tec-91,739

FAMAS1,552

Galil AR1,264

Lifetime map wins

12,584dust2

5,637inferno

2,157nuke

1,183train

677vertigo

633office

312cbble

99italy

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

Faceit stats

Combat

170Matches

58%Win rate

1.24Avg K/D

87.0ADR

49%Headshot %

Clutches & streaks

46%1v1 clutch win

26%1v2 clutch win

6Longest win streak

Recent Faceit resultsLWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	40	58%	1.20	18.2
Dust2	36	58%	1.26	18.3
Ancient	22	50%	1.06	16.6
Inferno	18	61%	1.36	20.2
Anubis	15	60%	1.43	19.9
Nuke	14	64%	1.24	15.8
Train	12	50%	1.42	23.6
Overpass	5	80%	1.09	15.6

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.

23.1%Headshot accuracy

37.4%Accuracy (enemy spotted)

41.2%Spray accuracy

85.4%Counter-strafing

8.9°Preaim

567msReaction time

32.8%T opening success

48.1%CT opening success

0.32Enemies flashed / flash

3.1%Flash assists

9.44HE damage / grenade

3.52Flashes / 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 0.3199 — 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 32.8497% — below the 40% mark we flag

Spend your practice time on Anubis

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

40% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
mirage	13–2	0.10	33%	28 Aug →
dust2	5–13	-0.09	15%	28 Aug →
mirage	13–8	0.03	22%	27 Aug →
inferno	7–13	-0.03	9%	25 Aug →
cache	13–10	-0.03	20%	24 Aug →
nuke	1–13	-0.08	13%	23 Aug →
mirage	6–13	-0.05	32%	23 Aug →
nuke	11–13	0.00	14%	23 Aug →
dust2	11–13	0.02	38%	23 Aug →
mirage	13–6	0.04	18%	23 Aug →
ancient	13–6	0.11	13%	22 Aug →
nuke	14–16	0.04	28%	22 Aug →
cache	11–13	0.02	37%	22 Aug →
ancient	13–11	-0.01	25%	20 Aug →
dust2	11–13	0.04	17%	20 Aug →
nuke	16–14	-0.02	29%	20 Aug →
cache	13–9	0.01	17%	19 Aug →
dust2	9–13	0.02	21%	19 Aug →
ancient	1–13	-0.04	40%	19 Aug →
inferno	13–7	-0.01	13%	18 Aug →
inferno	13–6	0.09	30%	18 Aug →
dust2	13–6	0.06	28%	18 Aug →
dust2	13–6	0.05	34%	17 Aug →
ancient	7–13	0.02	12%	17 Aug →
inferno	11–13	0.01	25%	16 Aug →
nuke	9–13	-0.00	22%	16 Aug →
anubis	10–13	0.07	15%	16 Aug →
inferno	13–9	0.08	21%	16 Aug →
nuke	13–7	0.10	29%	16 Aug →
cache	13–7	-0.01	23%	16 Aug →
vertigo	12–16	0.01	21%	16 Aug →
mirage	13–6	0.02	19%	15 Aug →
ancient	13–7	0.03	19%	15 Aug →
mirage	13–9	-0.02	17%	15 Aug →
ancient	10–13	0.01	24%	15 Aug →
mirage	22–18	0.01	19%	15 Aug →
dust2	8–13	0.02	24%	14 Aug →
inferno	13–8	-0.07	25%	14 Aug →
mirage	4–13	0.02	27%	14 Aug →
ancient	13–6	0.09	19%	14 Aug →
anubis	12–12	0.01	24%	14 Aug →
anubis	12–12	0.04	14%	14 Aug →
inferno	5–13	-0.06	48%	14 Aug →
train	11–13	-0.05	20%	13 Aug →
mirage	13–2	0.02	34%	13 Aug →
mirage	5–13	-0.04	29%	12 Aug →
ancient	3–13	-0.04	32%	10 Aug →
mirage	3–13	-0.05	36%	9 Aug →
anubis	13–8	0.05	34%	9 Aug →
ancient	13–7	0.00	16%	9 Aug →
train	12–12	-0.01	23%	9 Aug →
dust2	13–8	-0.01	21%	9 Aug →
mirage	5–13	-0.06	23%	9 Aug →
ancient	13–9	-0.01	26%	9 Aug →
ancient	10–13	0.10	26%	8 Aug →
nuke	13–10	-0.00	18%	8 Aug →
inferno	7–13	0.07	22%	8 Aug →
dust2	13–5	0.05	18%	7 Aug →
mirage	13–7	0.03	14%	6 Aug →
cache	7–13	0.03	46%	6 Aug →
mirage	10–13	-0.00	29%	6 Aug →
dust2	13–4	0.03	23%	6 Aug →
ancient	9–13	0.07	23%	5 Aug →
nuke	13–11	-0.03	21%	5 Aug →
mirage	4–13	-0.03	25%	5 Aug →
inferno	13–3	0.03	25%	5 Aug →
mirage	6–13	-0.01	22%	4 Aug →
inferno	10–13	-0.01	25%	3 Aug →
dust2	13–9	-0.00	23%	3 Aug →
dust2	9–13	-0.00	18%	3 Aug →
cache	11–13	-0.01	29%	3 Aug →
nuke	13–9	0.02	21%	3 Aug →
mirage	12–16	0.04	29%	2 Aug →
dust2	12–16	-0.04	20%	2 Aug →
inferno	13–10	-0.01	15%	2 Aug →
dust2	13–7	0.00	11%	1 Aug →
train	6–13	0.03	25%	1 Aug →
nuke	13–11	0.05	25%	1 Aug →
nuke	13–8	-0.02	28%	1 Aug →
inferno	13–9	0.02	31%	1 Aug →
anubis	16–12	-0.02	14%	31 Jul →
inferno	11–13	0.01	18%	31 Jul →
inferno	8–13	-0.01	27%	31 Jul →
inferno	7–13	-0.03	19%	29 Jul →
dust2	13–10	0.11	14%	29 Jul →
mirage	1–13	-0.04	23%	28 Jul →
dust2	13–7	-0.00	28%	28 Jul →
nuke	2–13	-0.03	36%	28 Jul →
mirage	13–8	0.01	27%	28 Jul →
dust2	13–11	-0.04	23%	28 Jul →
nuke	15–15	0.07	15%	28 Jul →
inferno	7–13	0.01	17%	28 Jul →
ancient	13–11	-0.05	16%	28 Jul →
dust2	13–6	0.09	33%	28 Jul →
mirage	13–10	0.09	11%	28 Jul →
nuke	13–6	0.03	13%	28 Jul →
inferno	13–9	0.07	31%	28 Jul →
dust2	7–13	0.01	33%	27 Jul →
nuke	13–9	0.01	29%	27 Jul →
dust2	10–13	-0.03	24%	26 Jul →

Show all 100 matchesShow fewer

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches

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