YoukaiKouhai

YoukaiKouhai — CS2 Stats

76561198852968232[U:1:892702504]Steam profile ↗✓ No bans

425Tracked matches54%Win rate2023Tracked since
792Hours in CS17Hrs last 2 wks
CSDB Rating4.3 DevelopingSupport
Premier CS Rating10,992Blue band · top ~49.6% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 8 Sep 2026 (10 days ago). Ranks are recorded once per day this page is viewed.

0Premier CS Rating · 10,992 → 10,992
+11Tracked matches · now 425
+8.7ppWin rate · 44.8% → 53.6%
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. 30 days played since 21 Jul 2026. Come back after the next session and the change shows above.

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Rating over time

Premier CS Rating: 10,992 +2,346 22 Jul8 Sept · 18 days played
8,53112,079peak 12,07922 Jul8 Sept
12,545Peak Premier in tracked matches
30Days played since 2026-07-21

Premier CS Rating

  • 1,087 below peak (12,079)
  • +1,093 over 30 days · improving
  • Next: Purple band at 15,000 4,008 to go
  • Reached: Blue band · Light Blue band
  • Blue band first seen 2026-09-03
  • Light Blue band first seen 2026-09-03

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=19,543), 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 rate46.3%41.9%44.3%above
Shot accuracy0.7%9.6%11.8%11.1% short
Kill/death ratio0.900.981.030.13 short
Match win rate42.7%43.8%45.2%2.5% short

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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CSDB.GGYoukaiKouhaiPREMIER10,992 · Blue bandcsdb.gg/stats

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Performance scores

Aim44
Positioning46
Utility63

0–100 skill scores via Leetify.

Recent form

STEADY46486Last 10046%Win rateWWLLWTLWWT

Last 10 vs previous 10: 0pp win rate · +0.03 avg rating · +5.2pp headshot accuracy · −4ms reaction

Win rate 0pp 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

  • 32 · 60% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 20%
  • Avg reaction 655ms

Last 10

  • 532 · 50% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 21%
  • Avg reaction 688ms

Last 20

  • 1082 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 19%
  • Avg reaction 690ms

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 (+3 against its own average).

Aim4.4
Utility6.3
Positioning4.6
Opening Duels2.2
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

NiKo

Plays most like NiKo 69% playstyle similarity

Most alike: utility contribution, positioning profile.

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

T-side openings. Opening success drops from 44% on CT to 25% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 675ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 67% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim4.4
Positioning4.6
Utility6.3
Mechanics3.7
Opening Duels1.8
Win Impact6.2

Composite 4.3/10 (Developing), 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-0.02−0.02
first ⅓ avg 0.00 → last ⅓ avg -0.02
Reaction time674ms−25ms
first ⅓ avg 698ms → last ⅓ avg 674ms
Headshot accuracy18.4%+3.3%
first ⅓ avg 15.2% → last ⅓ avg 18.4%

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

0.35Best match rating · 2–0 · cache, 11 Sept
40%Best headshot accuracy · 2–0 · cache, 11 Sept
430msFastest reaction time · 11–13 · nuke, 28 Aug
13–1Biggest win · train, 11 Sept

Across the last 100 tracked matches.

Highlights

5Longest win streak
W2Current streak
38In matches decided by ≤2 rounds
2Overtime games

Map breakdown

infernoBest map · 73% over 11officeWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
dust2A26151158%-0.00
nukeC1761135%-0.02
mirageA148657%-0.02
ancientD113827%-0.03
infernoS118373%0.00
trainC52340%-0.05
officeD51420%-0.06
cacheC52340%0.04
anubis3030%-0.04
overpass1010%-0.03
italy110100%0.02
vertigo1010%-0.04

Across the last 100 tracked matches.

Lifetime stats

22,682Lifetime kills
0.90K/D
1,812Matches
42.7%Match win rate
46.3%Headshot % · Top 50% of Blue band
0.7%Shot accuracy
2,195MVPs
501Hours (in match)
1,528Bombs planted
224Bombs defused

Most-used weapons

Lifetime map wins

2,482dust2
1,207inferno
1,183vertigo
1,025nuke
451train
133office
18italy
5cbble

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

Faceit stats

Combat

3Matches
0%Win rate
0.45Avg K/D
54.7ADR
52%Headshot %

Clutches & streaks

0%1v1 clutch win
0%1v2 clutch win
0Longest win streak

Recent Faceit resultsLLLLL

MapMatchesWin rateAvg K/DAvg kills
Ancient20%0.475.5
Dust210%0.417.0

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.

17.7%Headshot accuracy
30.2%Accuracy (enemy spotted)
34.8%Spray accuracy
66.9%Counter-strafing
9.4°Preaim
675msReaction time
24.9%T opening success
44.3%CT opening success
0.61Enemies flashed / flash
8.1%Flash assists
6.43HE damage / grenade
14.60Flashes / 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 24.8966% — 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.

27% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategyAncient grenade lineups

Recent matches

MapScoreRatingHS%Date
nuke13–10-0.076%18 Sept
ancient7–20.0630%18 Sept
dust211–13-0.0918%18 Sept
train11–13-0.0424%17 Sept
dust213–6-0.0621%15 Sept
dust212–12-0.0914%15 Sept
office10–13-0.0217%11 Sept
train13–1-0.0222%11 Sept
cache2–00.3540%11 Sept
cache12–120.0020%11 Sept
dust213–60.0018%9 Sept
inferno13–40.0418%8 Sept
dust213–30.0320%8 Sept
ancient7–13-0.0617%8 Sept
dust213–9-0.0613%8 Sept
ancient8–13-0.0315%8 Sept
dust25–13-0.0313%7 Sept
inferno13–9-0.109%7 Sept
office0–8-0.1025%7 Sept
anubis10–130.0114%7 Sept
ancient13–4-0.0320%7 Sept
ancient4–12-0.0119%6 Sept
cache13–6-0.0231%6 Sept
ancient10–13-0.0316%5 Sept
office8–13-0.0716%5 Sept
mirage13–3-0.0219%4 Sept
inferno6–13-0.0825%4 Sept
dust213–70.0117%4 Sept
inferno13–11-0.0517%4 Sept
mirage6–13-0.0318%4 Sept
nuke10–130.0216%2 Sept
mirage13–6-0.006%2 Sept
nuke13–11-0.0218%2 Sept
nuke8–13-0.0314%2 Sept
dust212–12-0.0210%31 Aug
anubis6–13-0.0912%31 Aug
nuke13–30.0319%30 Aug
cache2–13-0.0317%30 Aug
nuke2–7-0.0017%30 Aug
overpass11–13-0.034%29 Aug
italy13–40.0215%29 Aug
train3–13-0.0738%29 Aug
mirage9–13-0.088%29 Aug
nuke13–16-0.027%29 Aug
vertigo10–13-0.0413%28 Aug
ancient8–13-0.0618%28 Aug
office0–13-0.050%28 Aug
ancient5–13-0.0915%28 Aug
nuke8–13-0.069%28 Aug
nuke7–13-0.0313%28 Aug
nuke11–13-0.0421%28 Aug
dust211–13-0.0516%28 Aug
mirage13–7-0.0413%28 Aug
inferno3–0-0.0014%28 Aug
cache8–13-0.0811%27 Aug
office11–3-0.0714%27 Aug
inferno9–40.0221%27 Aug
inferno9–30.1118%27 Aug
inferno8–80.0811%27 Aug
inferno8–80.0714%27 Aug
train13–9-0.067%24 Aug
train8–13-0.0512%24 Aug
nuke4–13-0.117%23 Aug
mirage13–6-0.0111%14 Aug
dust213–9-0.0121%14 Aug
inferno13–8-0.0312%14 Aug
mirage8–13-0.0417%14 Aug
anubis5–13-0.0412%12 Aug
nuke0–13-0.0614%12 Aug
dust213–1-0.0115%12 Aug
nuke13–30.0415%12 Aug
dust213–60.1211%12 Aug
dust213–80.0717%11 Aug
mirage13–90.0015%11 Aug
dust211–13-0.0119%8 Aug
dust213–7-0.0216%8 Aug
mirage13–80.0314%8 Aug
mirage14–16-0.0113%8 Aug
nuke13–10-0.0614%7 Aug
ancient9–130.0222%7 Aug
mirage13–2-0.0512%7 Aug
dust20–4-0.130%6 Aug
dust213–20.2112%6 Aug
dust28–130.0516%6 Aug
dust213–5-0.0216%5 Aug
dust213–70.0913%5 Aug
nuke1–13-0.0219%5 Aug
dust24–13-0.0517%5 Aug
mirage13–5-0.0510%5 Aug
nuke13–50.1217%26 Jul
dust212–12-0.0510%25 Jul
ancient10–13-0.0613%25 Jul
dust213–30.1118%23 Jul
dust29–13-0.0117%23 Jul
mirage6–13-0.0017%23 Jul
dust213–8-0.0128%22 Jul
mirage7–13-0.0123%22 Jul
nuke11–13-0.0516%21 Jul
ancient13–8-0.0616%21 Jul
inferno13–6-0.0114%21 Jul

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 →