Chloe — CS2 Stats

GB76561199469622788[U:1:1509357060]Steam profile ↗✓ No bans

501Tracked matches43%Win rate2026Tracked since

487Hours in CS20Hrs last 2 wks

CSDB Rating4.0 DevelopingPositional Player

Premier CS Rating8,460Light Blue band · top ~62.3% of ranked players (population est.)

Ladder ranks via Leetify

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Performance scores

Aim57

Positioning52

Utility13

0–100 skill scores via Leetify.

Recent form

STEADY44–52–4Last 10044%Win rateLTWLLLWWWL

Last 10 vs previous 10: +10pp win rate · −0.01 avg rating · +3.3pp headshot accuracy · +2ms reaction

Win rate +10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

1–3–1 · 20% win rate
Avg rating -0.02
Avg headshot accuracy 13%
Avg reaction 642ms

Last 10

4–5–1 · 40% win rate
Avg rating -0.03
Avg headshot accuracy 15%
Avg reaction 642ms

Last 20

7–11–2 · 35% win rate
Avg rating -0.03
Avg headshot accuracy 13%
Avg reaction 641ms

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 (+2.3 against its own average).

Aim5.7

Utility1.3

Positioning5.2

Opening Duels2.2

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.

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 85% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower aim profile; 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.

Reaction time. 643ms 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

Aim5.7

Positioning5.2

Utility1.3

Mechanics5.5

Opening Duels3.6

Win Impact2.6

Composite 4.0/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.00

first ⅓ avg -0.02 → last ⅓ avg -0.02

Reaction time651ms+2ms

first ⅓ avg 649ms → last ⅓ avg 651ms

Headshot accuracy12.8%+0.0%

first ⅓ avg 12.8% → last ⅓ avg 12.8%

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.

Personal bests

0.10Best match rating · 13–4 · dust2, 26 Oct →

29%Best headshot accuracy · 8–13 · cache, 10 Oct →

484msFastest reaction time · 8–13 · ancient, 17 Oct →

13–1Biggest win · mirage, 25 Oct →

Across the last 100 tracked matches.

Highlights

6Longest win streak

4–11In matches decided by ≤2 rounds

3Overtime games

Map breakdown

mirageBest map · 59% over 22anubisWeakest map · 27% over 15

Map	Grade	Played	Record	Win rate	Avg rating
mirage	A	22	13–9	59%	-0.00
dust2	B	20	9–11	45%	-0.02
cache	D	18	6–12	33%	-0.03
anubis	D	15	4–11	27%	-0.04
ancient	A	14	8–6	57%	0.01
inferno	D	7	2–5	29%	-0.03
nuke	—	3	2–1	67%	-0.01
train	—	1	0–1	0%	-0.08

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (27% over 15). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

9,680Lifetime kills

0.76K/D

782Matches

43.0%Match win rate

35.5%Headshot %

0.0%Shot accuracy

1,030MVPs

261Hours (in match)

719Bombs planted

111Bombs defused

Most-used weapons

AK-473,470

M4A4 / M4A1-S2,555

Desert Eagle953

P2000 / USP-S502

Glock-18428

Galil AR327

AWP288

FAMAS150

AUG94

MP793

Lifetime map wins

1,726dust2

266inferno

224nuke

18vertigo

11train

10ar_shoots

5ar_baggage

3office

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

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

12.7%Headshot accuracy

36.6%Accuracy (enemy spotted)

39.3%Spray accuracy

74.9%Counter-strafing

10.2°Preaim

643msReaction time

48.1%T opening success

40.7%CT opening success

0.34Enemies flashed / flash

0.8%Flash assists

2.24HE damage / grenade

1.62Flashes / 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.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 12.6751% — below the 15% mark we flag
Aim Training →
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 0.3436 — below the 0.5 mark we flag
Grenade Lineups →

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.

27% win rate across 15 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
cache	11–13	0.03	10%	13 Nov →
anubis	12–12	-0.04	13%	13 Nov →
ancient	13–5	-0.04	13%	12 Nov →
dust2	10–13	-0.04	11%	12 Nov →
mirage	7–13	-0.02	16%	12 Nov →
cache	8–13	-0.02	14%	12 Nov →
dust2	13–10	-0.02	29%	11 Nov →
cache	13–11	-0.05	9%	11 Nov →
inferno	13–7	-0.03	18%	11 Nov →
train	3–13	-0.08	17%	4 Nov →
inferno	7–13	-0.01	13%	4 Nov →
anubis	11–13	-0.05	14%	4 Nov →
nuke	13–11	-0.01	11%	3 Nov →
mirage	13–8	-0.04	17%	3 Nov →
ancient	9–13	0.02	17%	3 Nov →
mirage	9–13	-0.03	8%	3 Nov →
mirage	13–9	0.02	17%	3 Nov →
anubis	8–13	0.01	10%	3 Nov →
ancient	12–12	-0.03	6%	3 Nov →
ancient	4–13	-0.06	4%	1 Nov →
dust2	13–10	-0.03	11%	1 Nov →
cache	13–7	-0.02	5%	1 Nov →
inferno	7–13	-0.07	8%	1 Nov →
mirage	13–5	-0.02	4%	1 Nov →
anubis	13–10	-0.03	17%	1 Nov →
inferno	6–13	-0.03	14%	1 Nov →
dust2	10–13	-0.01	23%	1 Nov →
nuke	10–13	-0.02	11%	30 Oct →
ancient	16–13	0.06	12%	30 Oct →
dust2	11–13	-0.05	7%	30 Oct →
anubis	9–13	-0.07	17%	30 Oct →
cache	13–3	-0.01	14%	30 Oct →
mirage	13–9	-0.00	13%	30 Oct →
nuke	16–12	0.00	14%	29 Oct →
inferno	5–13	0.02	6%	29 Oct →
mirage	13–7	0.04	14%	29 Oct →
anubis	11–13	-0.03	2%	29 Oct →
ancient	13–9	0.02	8%	29 Oct →
dust2	12–12	-0.03	4%	29 Oct →
cache	9–13	-0.04	15%	28 Oct →
dust2	13–11	-0.07	10%	28 Oct →
dust2	13–4	0.10	19%	26 Oct →
anubis	13–9	-0.06	10%	25 Oct →
mirage	13–3	-0.01	11%	25 Oct →
mirage	13–8	0.01	13%	25 Oct →
dust2	13–2	-0.03	18%	25 Oct →
cache	6–13	-0.01	18%	25 Oct →
ancient	13–10	0.04	13%	25 Oct →
dust2	10–13	-0.02	11%	25 Oct →
mirage	13–1	0.07	18%	25 Oct →
dust2	8–13	-0.06	4%	25 Oct →
mirage	2–13	-0.07	4%	25 Oct →
ancient	7–13	0.00	19%	23 Oct →
anubis	7–13	0.06	15%	23 Oct →
cache	5–13	-0.02	10%	23 Oct →
anubis	14–16	-0.08	9%	22 Oct →
anubis	12–12	-0.03	17%	22 Oct →
cache	6–13	-0.01	12%	22 Oct →
cache	11–13	-0.05	5%	18 Oct →
ancient	13–11	-0.01	10%	18 Oct →
cache	13–2	-0.04	29%	18 Oct →
inferno	13–5	-0.06	5%	18 Oct →
cache	13–6	0.01	11%	18 Oct →
mirage	13–8	0.03	7%	18 Oct →
ancient	8–13	-0.01	10%	17 Oct →
mirage	7–13	0.00	15%	17 Oct →
anubis	13–6	0.04	11%	17 Oct →
dust2	5–13	-0.05	23%	17 Oct →
anubis	9–13	-0.06	18%	16 Oct →
dust2	11–13	-0.01	13%	16 Oct →
mirage	1–13	0.02	11%	16 Oct →
dust2	13–3	-0.01	7%	13 Oct →
inferno	11–13	-0.05	5%	13 Oct →
dust2	13–7	-0.04	5%	13 Oct →
mirage	10–13	-0.01	12%	11 Oct →
dust2	13–9	-0.03	8%	11 Oct →
ancient	10–13	0.08	12%	11 Oct →
ancient	13–6	0.03	11%	11 Oct →
cache	8–13	0.09	29%	10 Oct →
dust2	10–13	0.01	20%	10 Oct →
cache	11–13	-0.03	13%	10 Oct →
mirage	4–13	-0.06	21%	9 Oct →
anubis	9–13	-0.08	15%	9 Oct →
dust2	5–13	-0.03	7%	9 Oct →
cache	4–13	-0.07	6%	9 Oct →
mirage	11–13	0.02	6%	9 Oct →
dust2	4–13	-0.05	5%	7 Oct →
anubis	5–13	-0.10	9%	7 Oct →
mirage	13–2	-0.02	17%	7 Oct →
mirage	10–13	-0.06	13%	4 Oct →
dust2	13–5	0.02	19%	4 Oct →
mirage	6–3	0.01	29%	4 Oct →
ancient	13–8	0.07	13%	4 Oct →
cache	6–13	-0.08	10%	4 Oct →
cache	13–4	-0.10	11%	30 Sept →
ancient	13–4	-0.01	8%	30 Sept →
mirage	13–3	0.06	14%	30 Sept →
mirage	13–9	0.00	11%	28 Sept →
anubis	13–3	-0.08	14%	28 Sept →
cache	11–13	-0.07	8%	28 Sept →