BallSackBandit02 — CS2 Stats

76561198413810171[U:1:453544443]Steam profile ↗✓ No bans

1,292Tracked matches63%Win rate2020Tracked since

2,067Hours in CS

CSDB Rating5.2 DevelopingAll-Rounder

FaceitLevel 9Top 20.7% of ranked FACEIT players

Ladder ranks via Leetify

Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 37 days played since 25 May 2025. Come back after the next session and the change shows above.

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Rating over time

Premier CS Rating: 20,110 -726 25 May – 14 Jul · 22 days played

21,484Peak Premier in tracked matches

37Days played since 2025-05-25

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

How this compares with the same rank

Median values for Level 9 among CSDB-tracked players (n=13,804), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

Metric	This player	Level 9 median	Level 10 median	vs Level 10
Headshot rate	47.9%	48.3%	51.0%	3.0% short
Shot accuracy	10.2%	13.2%	13.7%	3.5% short
Kill/death ratio	0.86	1.07	1.09	0.23 short
Match win rate	42.1%	46.9%	48.4%	6.3% short

This profile sits below the typical Level 10 player on every metric we can compare.

Widest gap: Shot accuracy. That is the metric furthest from the Level 10 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim58

Positioning50

Utility29

0–100 skill scores via Leetify.

Recent form

COLD48–50–2Last 10048%Win rateLLLWLLLWLL

Last 10 vs previous 10: −60pp win rate · −0.07 avg rating · −1.5pp headshot accuracy · +78ms reaction

Win rate down 60pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

1–4 · 20% win rate
Avg rating -0.04
Avg headshot accuracy 11%
Avg reaction 697ms

Last 10

2–8 · 20% win rate
Avg rating -0.05
Avg headshot accuracy 14%
Avg reaction 668ms

Last 20

10–10 · 50% win rate
Avg rating -0.02
Avg headshot accuracy 15%
Avg reaction 629ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: All-Rounder — No style dimension stands clear of the others in this profile.

Aim5.8

Utility2.9

Positioning5.0

Opening Duels4.1

Clutch5.0

Strong T-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.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

Plays most like donk 92% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower aim profile; 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

Reaction time. 610ms 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

Aim5.8

Positioning5.0

Utility2.9

Mechanics6.0

Opening Duels2.3

Win Impact9.4

Composite 5.2/10 (Developing), 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 -0.00 → last ⅓ avg -0.01

Reaction time623ms+22ms

first ⅓ avg 601ms → last ⅓ avg 623ms

Headshot accuracy15.5%+0.6%

first ⅓ avg 15.0% → last ⅓ avg 15.5%

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.

Personal bests

0.13Best match rating · 9–5 · vertigo, 15 Jul →

39%Best headshot accuracy · 7–13 · mirage, 17 Jul →

438msFastest reaction time · 7–13 · mirage, 17 Jul →

13–1Biggest win · dust2, 9 Aug →

Across the last 100 tracked matches.

Highlights

5Longest win streak

L3Current streak

10–10In matches decided by ≤2 rounds

9Overtime games

Map breakdown

nukeBest map · 64% over 14anubisWeakest map · 29% over 7

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	22	9–13	41%	0.00
dust2	A	21	12–9	57%	0.00
ancient	A	16	9–7	56%	0.00
nuke	A	14	9–5	64%	0.01
inferno	C	8	3–5	38%	-0.04
anubis	D	7	2–5	29%	-0.00
train	D	6	2–4	33%	-0.03
vertigo	—	2	1–1	50%	0.02
overpass	—	2	0–2	0%	-0.00
office	—	1	0–1	0%	-0.04
brewery	—	1	1–0	100%	-0.01

Across the last 100 tracked matches.

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

Lifetime stats

94,696Lifetime kills

0.86K/D

3,897Matches

42.1%Match win rate

47.9%Headshot %

10.2%Shot accuracy

9,833MVPs

2,067Hours (in match)

2,472Bombs planted

1,010Bombs defused

Most-used weapons

AK-4735,288

M4A4 / M4A1-S12,409

AWP10,138

P2000 / USP-S8,019

Desert Eagle6,198

Glock-183,267

SG 5533,172

MP92,014

Galil AR1,906

FAMAS1,406

Lifetime map wins

5,062inferno

3,661vertigo

2,699train

2,690nuke

2,554dust2

1,547office

339cbble

43lake

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

Faceit stats

Combat

464Matches

53%Win rate

1.03Avg K/D

79.9ADR

41%Headshot %

Clutches & streaks

45%1v1 clutch win

17%1v2 clutch win

8Longest win streak

Recent Faceit resultsWWLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	49	47%	0.98	13.9
Ancient	47	62%	1.02	14.7
Dust2	34	38%	1.08	16.9
Anubis	31	55%	1.12	15.0
Nuke	29	55%	1.10	17.2
Inferno	15	53%	0.91	12.3
Train	12	83%	1.18	16.7
Vertigo	8	88%	1.10	14.8

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.

15.4%Headshot accuracy

32.9%Accuracy (enemy spotted)

35.6%Spray accuracy

77.0%Counter-strafing

9.9°Preaim

610msReaction time

40.6%T opening success

37.4%CT opening success

0.62Enemies flashed / flash

6.5%Flash assists

8.37HE damage / grenade

7.99Flashes / 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
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 37.3973% — 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.

29% win rate across 7 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	5–13	-0.10	3%	24 Apr →
inferno	7–13	-0.05	13%	24 Apr →
mirage	10–13	-0.04	17%	14 Apr →
dust2	13–6	-0.02	6%	14 Apr →
mirage	3–13	0.02	16%	9 Apr →
inferno	2–9	-0.16	19%	17 Sept →
vertigo	6–9	-0.09	19%	17 Sept →
dust2	13–8	-0.02	20%	17 Sept →
mirage	3–13	0.02	15%	16 Sept →
train	4–13	-0.06	16%	7 Sept →
inferno	13–6	-0.03	18%	10 Aug →
nuke	13–5	0.01	22%	10 Aug →
office	6–13	-0.04	13%	9 Aug →
mirage	13–3	0.07	11%	9 Aug →
dust2	13–1	0.01	14%	9 Aug →
dust2	13–9	0.01	20%	28 Jul →
mirage	13–11	0.03	20%	25 Jul →
ancient	13–8	0.06	8%	18 Jul →
overpass	5–13	0.04	17%	18 Jul →
ancient	13–8	0.02	14%	17 Jul →
mirage	7–13	-0.08	39%	17 Jul →
dust2	13–3	0.01	15%	17 Jul →
inferno	5–9	0.01	14%	16 Jul →
nuke	13–8	-0.03	10%	16 Jul →
mirage	13–10	0.00	20%	16 Jul →
vertigo	9–5	0.13	31%	15 Jul →
overpass	5–9	-0.04	7%	15 Jul →
brewery	9–7	-0.01	10%	15 Jul →
inferno	9–2	-0.02	6%	15 Jul →
nuke	7–9	-0.04	23%	15 Jul →
ancient	16–14	0.09	15%	14 Jul →
nuke	13–6	0.07	14%	11 Jul →
ancient	12–16	-0.06	10%	11 Jul →
nuke	13–6	0.11	16%	11 Jul →
dust2	5–13	-0.03	20%	11 Jul →
mirage	13–7	0.03	6%	9 Jul →
ancient	13–11	-0.03	14%	5 Jul →
mirage	13–5	0.01	19%	5 Jul →
mirage	12–12	0.00	8%	5 Jul →
anubis	5–13	-0.08	14%	4 Jul →
dust2	16–13	0.01	26%	29 Jun →
mirage	11–13	-0.07	12%	28 Jun →
nuke	8–13	-0.01	23%	28 Jun →
mirage	13–10	0.02	14%	27 Jun →
ancient	8–13	-0.06	16%	27 Jun →
dust2	7–13	-0.01	10%	27 Jun →
ancient	16–14	0.04	17%	26 Jun →
dust2	13–11	0.04	18%	26 Jun →
nuke	13–11	-0.06	11%	26 Jun →
dust2	13–1	0.06	30%	26 Jun →
train	3–13	-0.03	16%	25 Jun →
anubis	11–13	0.02	10%	25 Jun →
mirage	16–14	0.01	16%	24 Jun →
nuke	13–8	0.08	7%	24 Jun →
anubis	13–5	0.03	4%	24 Jun →
nuke	10–13	-0.01	22%	23 Jun →
ancient	13–5	0.02	26%	23 Jun →
dust2	13–11	0.05	21%	23 Jun →
mirage	11–13	0.01	14%	23 Jun →
mirage	11–13	0.03	14%	15 Jun →
dust2	10–13	-0.03	17%	15 Jun →
dust2	13–2	0.03	22%	14 Jun →
anubis	13–10	0.06	10%	14 Jun →
ancient	13–11	-0.05	15%	14 Jun →
anubis	7–13	-0.01	20%	14 Jun →
inferno	9–13	-0.04	13%	13 Jun →
ancient	13–5	0.05	16%	13 Jun →
mirage	9–13	-0.02	15%	13 Jun →
dust2	7–13	-0.03	23%	13 Jun →
dust2	13–4	0.02	15%	13 Jun →
inferno	4–13	0.03	18%	11 Jun →
anubis	7–13	-0.04	8%	31 May →
train	11–13	0.01	13%	30 May →
anubis	10–13	-0.01	18%	30 May →
ancient	6–13	0.00	9%	30 May →
mirage	13–7	0.00	18%	30 May →
mirage	11–13	0.00	15%	30 May →
ancient	15–15	0.01	16%	30 May →
train	13–8	-0.02	17%	30 May →
dust2	10–13	-0.05	8%	30 May →
dust2	11–13	0.01	22%	29 May →
mirage	13–10	0.04	20%	29 May →
nuke	13–6	0.01	10%	29 May →
inferno	16–13	-0.03	6%	29 May →
dust2	3–13	-0.02	12%	29 May →
ancient	8–13	-0.03	24%	29 May →
train	5–13	-0.04	14%	29 May →
dust2	11–13	0.06	15%	29 May →
dust2	13–10	-0.04	22%	28 May →
train	13–6	-0.02	19%	28 May →
nuke	12–16	-0.02	19%	28 May →
ancient	11–13	-0.04	4%	28 May →
mirage	9–13	0.03	5%	27 May →
nuke	13–4	0.05	19%	27 May →
ancient	8–13	-0.04	18%	26 May →
ancient	13–3	0.09	11%	26 May →
mirage	2–13	0.03	12%	26 May →
dust2	6–13	0.03	25%	25 May →
nuke	12–16	-0.01	13%	25 May →
nuke	13–7	0.01	12%	25 May →