Lee Chae Young - 이채영

Lee Chae Young - 이채영 — CS2 Stats

KR76561199572302781[U:1:1612037053]Steam profile ↗✓ No bans

627Tracked matches61%Win rate2023Tracked since
564Hours in CS6Hrs last 2 wks
CSDB Rating6.8 SolidSupport
Premier CS Rating14,999Blue band · top ~28.4% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 16 Sep 2026 (3 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

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. 45 days played since 12 Mar 2026. Come back after the next session and the change shows above.

Is this you? Sign in with Steam to claim it and connect match tracking →

Rating over time

Premier CS Rating: 14,999 +4,313 12 Mar16 Sept · 18 days played
10,68614,999peak 14,99912 Mar16 Sept
14,999Peak Premier in tracked matches
45Days played since 2026-03-12

Premier CS Rating

  • At peak — 14,999
  • +3,638 over 90 days
  • Next: Purple band at 15,000 1 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.

How this compares with the same rank

Median values for Blue band among CSDB-tracked players (n=19,962), 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.

MetricThis playerBlue band medianPurple band medianvs Purple band
Headshot rate70.3%41.9%44.3%above
Shot accuracy0.0%9.6%11.8%11.8% short
Kill/death ratio1.080.981.03above
Match win rate48.8%43.8%45.2%above

This profile matches the typical Purple band player on 3 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.

Share this profile

CSDB.GGLee Chae Young - 이채영PREMIER14,999 · Blue bandcsdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim87
Positioning54
Utility65

0–100 skill scores via Leetify.

Recent form

HOT57385Last 10057%Win rateWWLWLLWWWW

Last 10 vs previous 10: +40pp win rate · +0.02 avg rating · +5.0pp headshot accuracy · −65ms reaction

Win rate up 40pp 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

  • 32 · 60% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 28%
  • Avg reaction 561ms

Last 10

  • 73 · 70% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 33%
  • Avg reaction 553ms

Last 20

  • 1091 · 50% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 30%
  • Avg reaction 586ms

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: SupportUtility contribution stands above the rest of this profile (+1.2 against its own average).

Aim8.7
Utility6.5
Positioning5.4
Opening Duels3.9

Sharp aimerExcellent counter-strafingEffective flashes

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

device

Plays most like device 92% playstyle similarity

Most alike: opening-duel success, 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

Strengths

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

Areas to improve

Positioning. Positioning trails aim by 33 points — deaths here waste a strong aim profile.

Reaction time. 606ms 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
Positioning5.4
Utility6.5
Mechanics8.7
Opening Duels3.8
Win Impact8.6

Composite 6.8/10 (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 rating-0.00−0.03
first ⅓ avg 0.03 → last ⅓ avg -0.00
Reaction time608ms−76ms
first ⅓ avg 684ms → last ⅓ avg 608ms
Headshot accuracy32.3%−0.5%
first ⅓ avg 32.8% → last ⅓ avg 32.3%

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

0.21Best match rating · 9–2 · inferno, 13 May
56%Best headshot accuracy · 13–8 · mirage, 4 Sept
438msFastest reaction time · 6–13 · inferno, 27 Aug
13–1Biggest win · mirage, 16 Sept

Across the last 100 tracked matches.

Highlights

7Longest win streak
W2Current streak
25In matches decided by ≤2 rounds
4Overtime games

Map breakdown

anubisBest map · 67% over 12trainWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
mirageB21101148%0.02
dust2A1810856%0.02
ancientB126650%0.02
anubisS128467%0.02
vertigoS96367%0.02
trainD72529%0.02
infernoS64267%0.05
cacheS64267%0.03
nukeA53260%-0.02
office330100%-0.00
overpass110100%0.10

Across the last 100 tracked matches.

Lifetime stats

15,239Lifetime kills
1.08K/D · Top 50% of Blue band
902Matches
48.8%Match win rate · Top 25% of Blue band
70.3%Headshot % · Top 1% of Blue band
0.0%Shot accuracy
2,069MVPs
305Hours (in match)
412Bombs planted
189Bombs defused

Most-used weapons

Lifetime map wins

1,467dust2
652vertigo
445inferno
380nuke
185train
65office
1ar_baggage

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.

32.1%Headshot accuracy
33.3%Accuracy (enemy spotted)
30.8%Spray accuracy
89.4%Counter-strafing
8.0°Preaim
606msReaction time
39.6%T opening success
51.1%CT opening success
0.74Enemies flashed / flash
5.0%Flash assists
11.12HE damage / grenade
14.54Flashes / 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.

  1. 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 39.5909% — below the 40% mark we flag

Spend your practice time on Train

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.

Train callouts & strategy

Recent matches

MapScoreRatingHS%Date
ancient13–6-0.0324%16 Sept
mirage13–10.0227%16 Sept
dust29–13-0.0435%14 Sept
anubis13–4-0.0819%14 Sept
mirage5–13-0.0233%14 Sept
inferno10–130.0637%14 Sept
dust213–50.0826%14 Sept
ancient16–120.0935%10 Sept
dust213–1-0.0536%4 Sept
mirage13–80.0256%4 Sept
nuke13–8-0.0535%4 Sept
dust213–5-0.0130%28 Aug
inferno6–13-0.0029%27 Aug
dust213–70.0127%27 Aug
cache10–130.0123%27 Aug
ancient13–160.0523%25 Aug
mirage0–13-0.0326%20 Aug
dust26–13-0.0428%20 Aug
anubis2–13-0.0733%20 Aug
nuke12–12-0.0124%20 Aug
ancient7–13-0.0533%20 Aug
dust213–50.0233%18 Aug
train13–50.0214%18 Aug
train12–12-0.0249%18 Aug
nuke13–90.0440%6 Aug
ancient2–13-0.0350%6 Aug
mirage13–50.0834%6 Aug
dust213–60.1232%1 Aug
vertigo13–30.0227%29 Jul
vertigo13–6-0.0640%29 Jul
vertigo2–13-0.0650%29 Jul
anubis6–13-0.0231%24 Jul
anubis13–90.0327%24 Jul
anubis12–12-0.0226%24 Jul
mirage11–20.0419%19 Jul
mirage12–120.0341%19 Jul
dust21–13-0.030%19 Jul
ancient13–40.1234%17 Jul
ancient9–130.0319%14 Jul
mirage11–130.1426%14 Jul
dust211–13-0.0035%14 Jul
mirage6–130.0326%4 Jul
overpass13–50.1032%4 Jul
mirage16–13-0.0129%29 Jun
dust28–130.1215%29 Jun
mirage13–50.0515%29 Jun
inferno13–10.0135%26 Jun
mirage7–13-0.1333%26 Jun
anubis13–20.0323%24 Jun
anubis13–50.0439%24 Jun
vertigo13–100.0137%24 Jun
mirage13–90.0039%23 Jun
train2–13-0.0340%23 Jun
train12–120.0539%23 Jun
ancient13–9-0.0230%20 Jun
train7–60.0733%17 Jun
mirage8–13-0.0426%15 Jun
ancient13–80.1128%15 Jun
anubis13–100.0633%15 Jun
dust28–130.0519%8 Jun
vertigo11–130.0238%8 Jun
vertigo13–60.0927%8 Jun
anubis9–130.0229%31 May
anubis13–60.1033%31 May
dust213–60.0232%26 May
mirage13–11-0.0433%26 May
inferno13–80.0023%26 May
mirage9–13-0.0238%22 May
office13–8-0.0126%13 May
office13–100.0135%13 May
inferno9–20.2138%13 May
cache13–40.0626%12 May
cache13–90.0144%6 May
cache7–13-0.0219%6 May
cache13–20.1045%3 May
dust26–13-0.0228%3 May
dust213–20.0150%3 May
cache13–20.0126%3 May
mirage10–130.0935%25 Apr
train5–13-0.0334%25 Apr
train13–60.0734%25 Apr
ancient3–13-0.0622%20 Apr
dust24–130.0138%20 Apr
inferno13–40.0550%15 Apr
mirage13–9-0.0423%14 Apr
vertigo13–8-0.0825%10 Apr
vertigo9–00.1019%10 Apr
vertigo2–70.1310%8 Apr
mirage8–13-0.0538%8 Apr
nuke13–6-0.0123%7 Apr
anubis13–10.1338%4 Apr
dust213–40.0946%4 Apr
ancient16–140.0342%25 Mar
dust213–70.0429%22 Mar
anubis11–7-0.0134%22 Mar
office13–4-0.0143%18 Mar
mirage11–130.1340%17 Mar
ancient5–130.0333%17 Mar
nuke7–13-0.0618%12 Mar
mirage13–60.0833%12 Mar

Match data via Leetify.

Recent teammates

Milestones

500 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →