Chick Ian — CS2 Stats

TR76561198428353986[U:1:468088258]Steam profile ↗✓ No bans

2,586Tracked matches52%Win rate2021Tracked since

2,625Hours in CS29Hrs last 2 wks

CSDB Rating5.4 DevelopingPositional Player

Premier CS Rating21,601Top 50% of 212,133 CSDB-tracked playersPink band · top ~6.7% of ranked players (population est.)

CSDB Leaderboard#61624 of 259052 tracked

WingmanLegendary Eagle Master

Ladder ranks via Leetify

What changed since last observed

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

−380Premier CS Rating · 21,981 → 21,601

Rating over time

Premier CS Rating: 21,601 +4,039 27 Aug – 31 Oct · 28 days played

Faceit ELO: 1,451 +0 31 Aug – 21 Sept · 5 observations

22,337Peak Premier in tracked matches

1,451Highest Faceit ELO seen on CSDB

24Days played since 2026-08-27

Premier CS Rating

736 below peak (22,337)
+1,487 over 30 days · improving
Next: Red band at 25,000 — 3,399 to go
Reached: Pink band · Purple band · Blue band · Light Blue band
Purple band first seen 2026-08-31
Blue band first seen 2026-08-31

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

How this compares with the same rank

Median values for Pink band among CSDB-tracked players (n=38,294), 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	Pink band median	Red band median	vs Red band
Headshot rate	39.4%	46.9%	49.3%	9.9% short
Shot accuracy	3.1%	13.0%	13.4%	10.2% short
Kill/death ratio	0.85	1.08	1.12	0.27 short
Match win rate	44.5%	46.7%	48.5%	4.0% short

This profile sits below the typical Red band player on every metric we can compare.

Widest gap: Shot accuracy. That is the metric furthest from the Red 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

Aim58

Positioning62

Utility44

0–100 skill scores via Leetify.

Recent form

STEADY54–43–3Last 10054%Win rateWLLWWLLLWT

Last 10 vs previous 10: −10pp win rate · −0.02 avg rating · −3.5pp headshot accuracy · +6ms 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

3–2 · 60% win rate
Avg rating -0.02
Avg headshot accuracy 9%
Avg reaction 592ms

Last 10

4–5–1 · 40% win rate
Avg rating -0.03
Avg headshot accuracy 10%
Avg reaction 567ms

Last 20

9–10–1 · 45% win rate
Avg rating -0.02
Avg headshot accuracy 12%
Avg reaction 564ms

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 (+2.1 against its own average).

Aim5.8

Utility4.4

Positioning6.2

Opening Duels3.2

Clutch2.6

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 Twistzz 83% 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. 563ms 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

Positioning6.2

Utility4.4

Mechanics5.3

Opening Duels3.3

Win Impact5.6

Composite 5.4/10 (Developing), 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 rating-0.01−0.00

first ⅓ avg -0.01 → last ⅓ avg -0.01

Reaction time564ms−18ms

first ⅓ avg 582ms → last ⅓ avg 564ms

Headshot accuracy12.4%−3.6%

first ⅓ avg 15.9% → last ⅓ avg 12.4%

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 · 13–7 · dust2, 3 Oct →

30%Best headshot accuracy · 3–13 · cache, 27 Sept →

430msFastest reaction time · 8–13 · nuke, 16 Oct →

13–2Biggest win · inferno, 16 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak

12–8In matches decided by ≤2 rounds

11Overtime games

Map breakdown

ancientBest map · 73% over 11infernoWeakest map · 40% over 20

Map	Grade	Played	Record	Win rate	Avg rating
dust2	A	21	12–9	57%	0.01
inferno	C	20	8–12	40%	-0.02
cache	C	17	7–10	41%	-0.02
nuke	B	12	6–6	50%	-0.02
ancient	S	11	8–3	73%	-0.01
anubis	S	9	6–3	67%	-0.02
mirage	A	5	3–2	60%	-0.01
poseidon	—	2	2–0	100%	0.01
office	—	1	0–1	0%	-0.09
rush_001	—	1	1–0	100%	0.02
eldorado	—	1	1–0	100%	0.07

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (40% over 20). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

52,579Lifetime kills

0.85K/D

3,653Matches

44.5%Match win rate

39.4%Headshot %

3.1%Shot accuracy

7,143MVPs

1,381Hours (in match)

4,212Bombs planted

861Bombs defused

Most-used weapons

AK-4713,296

M4A4 / M4A1-S10,999

AWP5,436

Desert Eagle3,464

P2000 / USP-S3,253

Glock-182,586

MP91,741

SSG 081,507

FAMAS1,176

MAC-101,175

Lifetime map wins

6,138dust2

6,053inferno

4,980nuke

2,705vertigo

1,066train

318lake

207cbble

201office

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

Faceit stats

Combat

169Matches

57%Win rate

0.85Avg K/D

67.7ADR

35%Headshot %

Clutches & streaks

33%1v1 clutch win

11%1v2 clutch win

11Longest win streak

Recent Faceit resultsLWLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	32	62%	0.91	13.3
Ancient	28	54%	0.88	13.4
Nuke	28	64%	0.96	14.2
Dust2	19	63%	0.84	12.8
Anubis	13	54%	0.78	11.4
Train	13	54%	1.05	15.2
Mirage	3	67%	0.85	14.0
Overpass	3	67%	0.88	11.3

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.

12.2%Headshot accuracy

33.0%Accuracy (enemy spotted)

35.9%Spray accuracy

73.7%Counter-strafing

9.4°Preaim

563msReaction time

38.0%T opening success

48.6%CT opening success

0.42Enemies flashed / flash

4.0%Flash assists

10.03HE damage / grenade

4.25Flashes / 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 12.1611% — 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 0.4179 — 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 37.9519% — below the 40% mark we flag

Spend your practice time on Inferno

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 20 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
ancient	13–7	0.05	9%	31 Oct →
cache	7–13	-0.07	10%	31 Oct →
anubis	10–13	-0.05	15%	31 Oct →
cache	13–11	-0.02	10%	30 Oct →
inferno	13–9	0.02	2%	30 Oct →
anubis	3–13	-0.05	5%	30 Oct →
office	4–13	-0.09	19%	30 Oct →
inferno	8–13	-0.05	21%	30 Oct →
nuke	13–11	-0.01	9%	30 Oct →
dust2	15–15	-0.03	6%	30 Oct →
cache	10–13	0.03	18%	30 Oct →
ancient	9–13	-0.03	18%	30 Oct →
ancient	13–7	0.01	18%	29 Oct →
inferno	13–9	0.01	14%	29 Oct →
anubis	13–11	-0.03	13%	29 Oct →
cache	9–13	-0.06	17%	29 Oct →
cache	7–13	-0.05	12%	27 Oct →
dust2	7–13	-0.02	18%	27 Oct →
inferno	16–14	-0.03	4%	25 Oct →
dust2	13–8	0.08	6%	25 Oct →
anubis	13–11	-0.02	7%	25 Oct →
dust2	13–10	0.10	12%	23 Oct →
inferno	11–13	-0.02	16%	23 Oct →
nuke	13–16	-0.08	4%	22 Oct →
cache	13–5	0.00	14%	22 Oct →
ancient	13–11	0.05	14%	22 Oct →
anubis	13–10	0.03	20%	18 Oct →
dust2	13–9	-0.01	9%	18 Oct →
inferno	6–13	-0.01	21%	18 Oct →
nuke	4–13	-0.04	13%	18 Oct →
dust2	11–13	0.01	8%	18 Oct →
cache	13–5	0.05	15%	18 Oct →
mirage	16–14	-0.03	12%	18 Oct →
inferno	15–15	-0.03	8%	18 Oct →
inferno	13–2	0.08	3%	16 Oct →
nuke	8–13	-0.09	9%	16 Oct →
mirage	5–13	-0.07	13%	16 Oct →
nuke	13–8	-0.05	2%	15 Oct →
dust2	13–5	0.01	7%	15 Oct →
nuke	14–16	-0.01	9%	13 Oct →
dust2	13–11	-0.01	23%	13 Oct →
anubis	13–10	0.04	11%	13 Oct →
nuke	13–4	0.04	23%	13 Oct →
ancient	5–13	-0.07	10%	11 Oct →
dust2	14–16	-0.07	9%	7 Oct →
nuke	14–16	-0.04	8%	7 Oct →
dust2	13–3	0.12	16%	6 Oct →
mirage	13–4	0.02	18%	6 Oct →
cache	9–13	-0.04	7%	6 Oct →
dust2	10–13	-0.06	17%	6 Oct →
cache	6–13	-0.01	10%	6 Oct →
dust2	13–2	0.01	14%	6 Oct →
dust2	13–7	0.13	19%	3 Oct →
cache	13–10	0.08	17%	3 Oct →
inferno	13–11	0.00	8%	3 Oct →
anubis	5–13	-0.04	11%	3 Oct →
inferno	3–13	-0.07	16%	3 Oct →
cache	13–9	-0.03	11%	28 Sept →
ancient	13–7	0.06	26%	28 Sept →
inferno	6–13	0.00	6%	28 Sept →
inferno	6–13	-0.10	28%	28 Sept →
ancient	4–13	-0.07	22%	28 Sept →
dust2	3–13	-0.10	13%	28 Sept →
nuke	5–0	0.06	13%	28 Sept →
cache	13–8	0.00	14%	27 Sept →
nuke	8–13	-0.02	11%	27 Sept →
inferno	15–15	-0.00	10%	27 Sept →
dust2	13–10	-0.07	5%	27 Sept →
cache	3–13	-0.09	30%	27 Sept →
dust2	13–10	0.01	13%	27 Sept →
mirage	10–13	-0.03	13%	25 Sept →
rush_001	8–7	0.02	11%	24 Sept →
inferno	6–9	-0.13	16%	24 Sept →
poseidon	9–7	-0.05	21%	24 Sept →
inferno	6–9	-0.05	16%	24 Sept →
inferno	14–16	-0.00	18%	24 Sept →
mirage	13–11	0.04	19%	24 Sept →
nuke	13–9	0.00	10%	24 Sept →
ancient	13–8	-0.01	7%	20 Sept →
dust2	14–16	0.07	26%	20 Sept →
dust2	13–7	-0.00	27%	20 Sept →
inferno	9–5	0.05	23%	9 Sept →
eldorado	9–5	0.07	15%	9 Sept →
poseidon	9–5	0.06	5%	9 Sept →
dust2	9–13	0.01	11%	9 Sept →
inferno	13–9	0.00	28%	9 Sept →
cache	8–13	-0.08	7%	31 Aug →
inferno	13–4	0.05	19%	31 Aug →
dust2	13–6	-0.00	10%	31 Aug →
dust2	8–13	-0.04	14%	28 Aug →
cache	13–5	-0.01	14%	28 Aug →
ancient	13–7	0.01	10%	28 Aug →
ancient	13–2	-0.06	15%	28 Aug →
nuke	13–6	-0.00	21%	28 Aug →
anubis	13–6	-0.02	19%	28 Aug →
cache	10–13	-0.06	21%	27 Aug →
ancient	13–9	0.00	13%	27 Aug →
inferno	11–13	-0.04	16%	27 Aug →
anubis	13–9	-0.00	21%	27 Aug →
cache	10–13	0.01	12%	27 Aug →