Alya Kujou

Alya Kujou — CS2 Stats

76561199176007974[U:1:1215742246]Steam profile ↗✓ No bans

108Tracked matches57%Win rate2025Tracked since
210Hours in CS10Hrs last 2 wks
CSDB Rating4.7 DevelopingPositional Player
Premier CS Rating4,718Grey band · top ~80% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 24 Sep 2026 (8 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.

Rating over time

Premier CS Rating: 4,718 +788 22 Aug – 24 Sept · 19 days played
3,5454,946peak 4,94622 Aug24 Sept
4,946Peak Premier in tracked matches
44Days played since 2026-06-21

Premier CS Rating

  • 228 below peak (4,946)
  • +681 over 30 days · improving
  • Next: Light Blue band at 5,000 — 282 to go

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 Grey band among CSDB-tracked players (n=3,645), 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 playerGrey band medianLight Blue band medianvs Light Blue band
Headshot rate46.3%38.2%39.9%above
Shot accuracy7.3%3.6%7.0%above
Kill/death ratio1.030.830.92above
Match win rate48.0%40.2%42.3%above

Across every metric we can compare, this profile already matches the typical Light Blue band player. Rank still comes from winning matches — this is a performance comparison, not a prediction.

Share this profile

CSDB.GGAlya KujouPREMIER4,718 · Grey bandcsdb.gg/stats

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Performance scores

Aim63
Positioning53
Utility20

0–100 skill scores via Leetify.

Recent form

STEADY46–51–3Last 10046%Win rateLLLLWLWWWL

Last 10 vs previous 10: −40pp win rate · −0.01 avg rating · −3.3pp headshot accuracy · +20ms reaction

Win rate down 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

  • 1–4 · 20% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 15%
  • Avg reaction 631ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 16%
  • Avg reaction 669ms

Last 20

  • 12–8 · 60% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 17%
  • Avg reaction 659ms

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 (+1.8 against its own average).

Aim6.3
Utility2.0
Positioning5.3
Opening Duels3.1

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

s1mple

Plays most like s1mple 88% 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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

CT openings. Opening success drops from 54% on T to 35% on CT — first contacts on the defending side are being lost.

Reaction time. 668ms 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

Aim6.3
Positioning5.3
Utility2.0
Mechanics5.9
Opening Duels3.7
Win Impact7.4

Composite 4.7/10 (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 rating0.00−0.01
first ⅓ avg 0.01 → last ⅓ avg 0.00
Reaction time673ms+36ms
first ⅓ avg 637ms → last ⅓ avg 673ms
Headshot accuracy18.9%+4.1%
first ⅓ avg 14.9% → last ⅓ avg 18.9%

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 · 9–6 · debris, 11 Aug →
48%Best headshot accuracy · 9–4 · inferno, 15 Sept →
406msFastest reaction time · 7–13 · ancient, 4 Sept →
13–0Biggest win · anubis, 20 Sept →

Across the last 100 tracked matches.

Highlights

4Longest win streak
L4Current streak
4–5In matches decided by ≤2 rounds
3Overtime games

Map breakdown

nukeBest map · 80% over 5ancientWeakest map · 13% over 8
MapGradePlayedRecordWin rateAvg rating
mirageB3016–1453%0.00
infernoB2010–1050%0.01
dust2C135–838%-0.01
anubisA117–464%0.02
cacheD82–625%-0.00
ancientD81–713%-0.01
nukeS54–180%0.03
vertigo—20–20%-0.01
train—20–20%-0.01
debris—11–0100%0.15

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (13% over 8). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

5,446Lifetime kills
1.03K/D · Top 25% of Grey band
346Matches
48.0%Match win rate · Top 10% of Grey band
46.3%Headshot % · Top 25% of Grey band
7.3%Shot accuracy · Top 50% of Grey band
470MVPs
102Hours (in match)
85Bombs planted
38Bombs defused

Most-used weapons

Lifetime map wins

314inferno
254dust2
176vertigo
173nuke
52cbble
27train
10office
6lake

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.

17.8%Headshot accuracy
37.0%Accuracy (enemy spotted)
40.4%Spray accuracy
76.3%Counter-strafing
10.9°Preaim
668msReaction time
54.2%T opening success
35.2%CT opening success
0.48Enemies flashed / flash
2.5%Flash assists
4.45HE damage / grenade
3.99Flashes / 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.

  1. 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 0.4827 — below the 0.5 mark we flag

    Grenade Lineups →
  2. Advanced Mechanics

    Losing the first CT duel repeatedly usually means holding angles that favour the peeker.

    CT opening duels 35.2264% — below the 40% mark we flag

Spend your practice time on Ancient

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

13% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage9–13-0.0316%24 Sept →
inferno5–13-0.1018%24 Sept →
anubis3–13-0.0618%22 Sept →
dust29–110.027%22 Sept →
inferno13–50.1119%21 Sept →
cache9–13-0.0717%21 Sept →
mirage13–60.0315%20 Sept →
anubis13–00.0015%20 Sept →
nuke13–80.0321%20 Sept →
vertigo10–13-0.0310%19 Sept →
inferno13–60.0119%19 Sept →
cache13–90.0416%19 Sept →
mirage13–5-0.0314%16 Sept →
inferno9–40.1348%15 Sept →
inferno6–9-0.0521%15 Sept →
inferno13–100.0415%15 Sept →
anubis13–80.0310%14 Sept →
dust213–9-0.0513%14 Sept →
dust213–8-0.0914%13 Sept →
dust25–13-0.0121%12 Sept →
cache13–80.0520%12 Sept →
anubis6–130.0117%10 Sept →
anubis12–12-0.0218%10 Sept →
cache8–13-0.0721%9 Sept →
dust216–140.0228%8 Sept →
mirage7–13-0.0228%8 Sept →
cache8–130.0418%7 Sept →
nuke13–30.0727%6 Sept →
nuke13–6-0.0014%6 Sept →
ancient12–12-0.0019%4 Sept →
mirage13–8-0.0215%4 Sept →
ancient7–13-0.0132%4 Sept →
anubis13–40.0621%4 Sept →
vertigo9–130.0124%3 Sept →
mirage7–13-0.060%3 Sept →
mirage8–13-0.0216%2 Sept →
inferno4–13-0.0930%1 Sept →
anubis13–30.0528%1 Sept →
mirage13–40.0516%31 Aug →
inferno13–50.0123%31 Aug →
inferno6–13-0.0219%30 Aug →
mirage13–40.0124%30 Aug →
nuke7–130.0215%30 Aug →
mirage13–8-0.0016%30 Aug →
mirage13–10.0521%30 Aug →
mirage7–130.034%30 Aug →
mirage13–70.0215%30 Aug →
dust213–40.0514%29 Aug →
inferno9–20.0524%29 Aug →
dust27–13-0.0728%28 Aug →
ancient9–13-0.0322%27 Aug →
inferno3–13-0.0317%25 Aug →
dust28–110.0022%25 Aug →
mirage3–13-0.0523%24 Aug →
mirage13–20.0419%24 Aug →
mirage3–13-0.0010%24 Aug →
mirage13–20.0234%24 Aug →
cache11–130.0516%23 Aug →
inferno13–4-0.0017%23 Aug →
mirage8–13-0.018%23 Aug →
cache7–130.0014%22 Aug →
dust216–140.0124%22 Aug →
inferno13–30.0214%22 Aug →
mirage13–11-0.0013%22 Aug →
mirage11–130.1014%21 Aug →
inferno8–13-0.093%21 Aug →
ancient4–13-0.0110%21 Aug →
ancient0–8-0.0319%20 Aug →
anubis13–60.1111%19 Aug →
mirage7–130.006%19 Aug →
mirage4–2-0.0014%19 Aug →
ancient13–10-0.0519%18 Aug →
mirage5–13-0.086%18 Aug →
mirage10–13-0.0816%18 Aug →
ancient9–130.0711%17 Aug →
mirage13–10.025%17 Aug →
dust28–13-0.0314%16 Aug →
anubis13–100.0612%16 Aug →
mirage13–10.0719%16 Aug →
inferno13–80.1210%16 Aug →
anubis7–13-0.0212%16 Aug →
train10–13-0.0311%15 Aug →
inferno11–130.0215%15 Aug →
dust27–130.0215%15 Aug →
mirage10–130.019%11 Aug →
ancient2–130.0011%11 Aug →
inferno4–90.1013%11 Aug →
anubis13–7-0.0011%11 Aug →
debris9–60.158%11 Aug →
mirage9–13-0.0214%10 Aug →
mirage13–80.0427%9 Aug →
inferno5–9-0.0414%9 Aug →
dust27–130.0016%6 Aug →
mirage13–10-0.0324%4 Aug →
cache12–16-0.0320%1 Aug →
nuke13–90.0522%1 Aug →
inferno13–70.0130%30 Jun →
train11–130.0029%23 Jun →
inferno8–8-0.0210%21 Jun →
dust29–13-0.0318%21 Jun →

Match data via Leetify.

Recent teammates

Milestones

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

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