Cheezy | CSFIT — CS2 Stats

US76561198080237475[U:1:119971747]Steam profile ↗✓ No bans

2,627Tracked matches46%Win rate2024Tracked since

3,387Hours in CS58Hrs last 2 wks

CSDB Rating6.0 SolidPositional Player

Premier CS Rating10,834Blue band · top ~50.5% of ranked players (population est.)

CSDB Leaderboard#181271 of 259662 tracked

WingmanMaster Guardian II

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 4 Oct 2026 (30 days ago). Ranks are recorded once per day this page is viewed.

+130Tracked matches · now 2,627

−11.5ppWin rate · 57.7% → 46.2%

Rating over time

11,060Peak Premier in tracked matches

22Days played since 2026-09-04

Premier CS Rating

At peak — 10,834
Next: Purple band at 15,000 — 4,166 to go
Reached: Blue band · Light Blue band

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

Compare periods

Last 30 days vs previous 30

Metric	Last 30	Previous 30	Change
Matches	204	218	−14
Win rate	47%	47%	−0pp
K/D	0.93	1.04	−0.11
Headshot %	45%	39%	+6pp

Measured 4 Oct 2026 → 3 Nov 2026; previous 4 Sep 2026 → 4 Oct 2026.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Blue band among CSDB-tracked players (n=21,222), 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	Blue band median	Purple band median	vs Purple band
Headshot rate	39.8%	42.0%	44.4%	4.6% short
Shot accuracy	0.2%	9.6%	11.9%	11.7% short
Kill/death ratio	0.95	0.98	1.03	0.09 short
Match win rate	46.2%	43.8%	45.2%	above

This profile matches the typical Purple band player on 1 of 4 comparable metrics.

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

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Performance scores

Aim67

Positioning64

Utility58

0–100 skill scores via Leetify.

Recent form

STEADY47–43–10Last 10047%Win rateLLWWTWLLWW

Last 10 vs previous 10: +20pp win rate · +0.04 avg rating · +3.8pp headshot accuracy · +40ms reaction

Win rate up 20pp 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

2–2–1 · 40% win rate
Avg rating 0.03
Avg headshot accuracy 20%
Avg reaction 653ms

Last 10

5–4–1 · 50% win rate
Avg rating 0.02
Avg headshot accuracy 20%
Avg reaction 617ms

Last 20

8–10–2 · 40% win rate
Avg rating -0.00
Avg headshot accuracy 18%
Avg reaction 597ms

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: Positional Player — Positioning stands above the rest of this profile (+2.4 against its own average).

Aim6.7

Utility5.8

Positioning6.4

Opening Duels3.9

Clutch0.0

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 Twistzz 86% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower opening-duel success; 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. 600ms 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

Aim6.7

Positioning6.4

Utility5.8

Mechanics7.7

Opening Duels6.1

Win Impact3.7

Composite 6.0/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.00−0.01

first ⅓ avg 0.01 → last ⅓ avg 0.00

Reaction time612ms+21ms

first ⅓ avg 591ms → last ⅓ avg 612ms

Headshot accuracy16.7%−2.3%

first ⅓ avg 18.9% → last ⅓ avg 16.7%

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

0.15Best match rating · 13–7 · cache, 31 Oct →

50%Best headshot accuracy · 13–4 · cache, 25 Oct →

383msFastest reaction time · 5–0 · nuke, 11 Oct →

13–1Biggest win · nuke, 1 Nov →

Across the last 100 tracked matches.

Highlights

6Longest win streak

L2Current streak

5–8In matches decided by ≤2 rounds

1Overtime games

Map breakdown

cacheBest map · 60% over 10anubisWeakest map · 33% over 6

Map	Grade	Played	Record	Win rate	Avg rating
nuke	B	24	11–13	46%	-0.01
office	B	24	11–13	46%	0.01
cache	A	10	6–4	60%	0.03
vertigo	C	7	3–4	43%	0.01
anubis	D	6	2–4	33%	0.00
overpass	D	6	2–4	33%	-0.01
train	A	5	3–2	60%	0.00
fachwerk	—	3	2–1	67%	0.04
italy	—	3	1–2	33%	0.01
dust2	—	3	1–2	33%	0.03
mirage	—	3	1–2	33%	0.01
inferno	—	2	1–1	50%	-0.03
ancient	—	2	1–1	50%	-0.02
boulder	—	1	1–0	100%	0.11
shelter	—	1	1–0	100%	0.09

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (33% over 6). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

56,328Lifetime kills

0.95K/D

4,347Matches

46.2%Match win rate · Top 50% of Blue band

39.8%Headshot %

0.2%Shot accuracy

9,152MVPs

2,093Hours (in match)

3,733Bombs planted

864Bombs defused

Most-used weapons

AK-4719,666

M4A4 / M4A1-S12,722

Desert Eagle3,454

AWP3,020

P2000 / USP-S2,832

Glock-182,315

Galil AR1,829

MP91,766

MAC-101,507

MAG-71,074

Lifetime map wins

6,355nuke

5,839office

4,236vertigo

1,979dust2

1,850inferno

1,033train

473italy

10ar_shoots

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

Faceit stats

Combat

7Matches

71%Win rate

1.04Avg K/D

82.8ADR

45%Headshot %

Clutches & streaks

0%1v1 clutch win

50%1v2 clutch win

2Longest win streak

Recent Faceit resultsWWLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	3	33%	1.02	22.3
Vertigo	1	100%	1.15	15.0
Inferno	1	100%	1.14	16.0
Mirage	1	100%	0.94	15.0
Nuke	1	100%	0.96	27.0

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.

17.2%Headshot accuracy

34.3%Accuracy (enemy spotted)

35.7%Spray accuracy

84.6%Counter-strafing

10.8°Preaim

600msReaction time

57.5%T opening success

51.1%CT opening success

0.60Enemies flashed / flash

16.1%Flash assists

11.40HE damage / grenade

5.52Flashes / match

Recommended for you

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.

33% win rate across 6 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
anubis	11–13	0.02	23%	3 Nov →
nuke	7–13	0.01	19%	3 Nov →
anubis	13–5	0.11	20%	3 Nov →
anubis	13–7	-0.02	15%	3 Nov →
nuke	15–15	0.04	24%	3 Nov →
office	13–2	0.05	22%	3 Nov →
office	6–13	-0.00	18%	3 Nov →
cache	4–13	-0.03	6%	3 Nov →
office	13–10	-0.05	29%	2 Nov →
cache	8–0	0.07	19%	2 Nov →
nuke	13–6	-0.13	0%	2 Nov →
cache	10–13	-0.04	18%	2 Nov →
office	11–13	0.03	15%	2 Nov →
nuke	10–13	-0.03	11%	2 Nov →
train	7–13	-0.03	16%	2 Nov →
fachwerk	9–13	0.01	20%	1 Nov →
office	12–12	0.03	27%	1 Nov →
nuke	13–1	-0.02	17%	1 Nov →
overpass	2–13	-0.09	8%	31 Oct →
vertigo	13–6	0.04	27%	31 Oct →
train	13–6	-0.06	17%	31 Oct →
office	13–11	-0.01	14%	31 Oct →
nuke	10–13	0.05	19%	31 Oct →
cache	13–7	0.15	17%	31 Oct →
office	8–13	0.00	20%	31 Oct →
office	12–12	0.04	13%	30 Oct →
italy	11–13	-0.02	12%	28 Oct →
nuke	11–13	0.01	17%	28 Oct →
vertigo	12–12	-0.03	13%	28 Oct →
cache	13–4	0.12	13%	27 Oct →
nuke	11–13	-0.10	15%	27 Oct →
dust2	13–4	0.04	13%	27 Oct →
overpass	12–12	-0.03	12%	27 Oct →
cache	13–8	0.07	8%	27 Oct →
nuke	13–9	-0.05	22%	27 Oct →
office	7–1	0.05	11%	27 Oct →
inferno	13–9	-0.06	30%	27 Oct →
overpass	13–5	0.08	7%	26 Oct →
office	13–5	-0.00	33%	26 Oct →
nuke	5–13	-0.03	12%	26 Oct →
anubis	4–13	-0.06	41%	26 Oct →
cache	13–4	0.03	20%	26 Oct →
italy	7–13	0.02	29%	26 Oct →
office	13–3	0.03	24%	26 Oct →
office	13–10	0.05	13%	26 Oct →
office	13–10	-0.04	14%	25 Oct →
cache	13–4	-0.01	50%	25 Oct →
nuke	13–11	-0.07	15%	25 Oct →
office	4–13	0.05	15%	24 Oct →
boulder	7–1	0.11	12%	24 Oct →
vertigo	10–13	-0.03	9%	24 Oct →
dust2	7–13	0.01	17%	24 Oct →
fachwerk	13–3	0.06	14%	24 Oct →
nuke	13–10	-0.03	9%	24 Oct →
train	13–11	0.02	23%	23 Oct →
fachwerk	13–8	0.04	10%	23 Oct →
mirage	12–12	-0.07	17%	23 Oct →
nuke	7–13	-0.05	19%	23 Oct →
shelter	13–10	0.09	22%	21 Oct →
office	9–13	-0.02	11%	21 Oct →
office	12–12	0.06	20%	21 Oct →
nuke	11–13	-0.01	13%	20 Oct →
office	13–8	-0.01	16%	20 Oct →
anubis	4–13	-0.00	4%	20 Oct →
vertigo	4–13	-0.06	12%	20 Oct →
nuke	7–13	0.04	10%	20 Oct →
nuke	13–5	0.01	18%	19 Oct →
nuke	13–8	0.03	16%	19 Oct →
office	8–13	0.01	16%	19 Oct →
nuke	4–0	0.07	25%	19 Oct →
dust2	12–12	0.03	21%	18 Oct →
train	6–13	0.07	24%	18 Oct →
overpass	4–13	-0.03	26%	18 Oct →
office	11–13	-0.01	24%	17 Oct →
vertigo	12–12	-0.05	17%	17 Oct →
nuke	4–13	-0.08	12%	17 Oct →
office	11–2	0.02	28%	17 Oct →
overpass	13–10	0.02	23%	17 Oct →
train	13–8	-0.00	34%	17 Oct →
office	11–13	0.05	24%	14 Oct →
nuke	1–8	0.02	20%	13 Oct →
overpass	6–13	-0.05	15%	13 Oct →
inferno	10–13	-0.00	11%	13 Oct →
ancient	13–3	0.00	19%	13 Oct →
anubis	8–13	-0.01	14%	13 Oct →
office	9–13	-0.05	45%	12 Oct →
nuke	5–13	-0.03	4%	11 Oct →
nuke	5–0	-0.03	25%	11 Oct →
italy	13–11	0.03	17%	11 Oct →
cache	2–5	0.01	25%	11 Oct →
ancient	7–13	-0.04	10%	11 Oct →
office	13–11	0.08	11%	11 Oct →
mirage	12–12	-0.07	19%	11 Oct →
cache	8–13	-0.05	17%	10 Oct →
vertigo	13–3	0.00	21%	10 Oct →
nuke	13–5	0.03	9%	10 Oct →
office	7–13	-0.03	13%	10 Oct →
vertigo	9–5	0.15	19%	9 Oct →
mirage	13–1	0.15	15%	9 Oct →
nuke	13–8	0.01	7%	9 Oct →