Kawi

Kawi — CS2 Stats

76561198286423897[U:1:326158169]Steam profile ↗✓ No bans

298Tracked matches64%Win rate2024Tracked since
808Hours in CS107Hrs last 2 wks
CSDB Rating5.4 DevelopingPositional Player
Premier CS Rating10,914Blue band · top ~50.1% of ranked players (population est.)
WingmanGold Nova I
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 6 Oct 2026 (6 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: 10,914 +2,210 30 Sept – 6 Oct · 7 days played
8,70410,914peak 10,91430 Sept6 Oct
11,287Peak Premier in tracked matches
13Days played since 2026-09-29

Premier CS Rating

  • At peak — 10,914
  • Next: Purple band at 15,000 — 4,086 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.

Compare periods

Last 30 days vs previous 30

MetricLast 30Previous 30Change
Matches162——
Win rate49%——
K/D1.10——
Headshot %34%——

Measured 13 Sep 2026 → 12 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Blue band among CSDB-tracked players (n=21,222), 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 rate36.2%42.0%44.3%8.1% short
Shot accuracy2.9%9.6%11.9%8.9% short
Kill/death ratio0.930.981.030.11 short
Match win rate41.0%43.8%45.2%4.2% short

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

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.GGKawiPREMIER10,914 · Blue bandcsdb.gg/stats

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Performance scores

Aim56
Positioning63
Utility36

0–100 skill scores via Leetify.

Recent form

STEADY51–42–7Last 10051%Win rateLWWWWLLLWL

Last 10 vs previous 10: 0pp win rate · +0.05 avg rating · +2.3pp headshot accuracy · +12ms 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

  • 4–1 · 80% win rate
  • Avg rating 0.04
  • Avg headshot accuracy 14%
  • Avg reaction 538ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 13%
  • Avg reaction 566ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 12%
  • Avg reaction 560ms

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 (+1.9 against its own average).

Aim5.6
Utility3.6
Positioning6.3
Opening Duels3.2

Strong CT-side openerLimited 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

jL

Plays most like jL 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

T-side openings. Opening success drops from 57% on CT to 41% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim5.6
Positioning6.3
Utility3.6
Mechanics5.2
Opening Duels4.7
Win Impact9.8

Composite 5.4/10 (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 rating0.01−0.02
first ⅓ avg 0.03 → last ⅓ avg 0.01
Reaction time563ms+34ms
first ⅓ avg 529ms → last ⅓ avg 563ms
Headshot accuracy11.6%−2.1%
first ⅓ avg 13.7% → last ⅓ avg 11.6%

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

0.18Best match rating · 6–2 · inferno, 1 Oct →
100%Best headshot accuracy · 6–2 · inferno, 1 Oct →
383msFastest reaction time · 6–2 · inferno, 1 Oct →
13–1Biggest win · office, 11 Oct →

Across the last 100 tracked matches.

Highlights

4Longest win streak
1–7In matches decided by ≤2 rounds
4Overtime games

Map breakdown

cacheBest map · 80% over 5nukeWeakest map · 39% over 18
MapGradePlayedRecordWin rateAvg rating
officeS2416–867%0.03
nukeC187–1139%0.06
infernoC156–940%-0.00
mirageC146–843%0.02
dust2A138–562%0.00
cacheS54–180%0.00
overpass—30–30%-0.09
anubis—31–233%0.03
train—22–0100%-0.01
debris—10–10%-0.21
vertigo—11–0100%0.12
ancient—10–10%0.10

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (39% over 18). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Lifetime stats

17,112Lifetime kills
0.93K/D
1,280Matches
41.0%Match win rate
36.2%Headshot %
2.9%Shot accuracy
1,864MVPs
336Hours (in match)
662Bombs planted
109Bombs defused

Most-used weapons

Lifetime map wins

1,868dust2
1,278office
692nuke
527vertigo
400inferno
162train
95lake
63cbble

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.

10.8%Headshot accuracy
33.0%Accuracy (enemy spotted)
31.2%Spray accuracy
73.2%Counter-strafing
8.8°Preaim
533msReaction time
41.0%T opening success
56.6%CT opening success
0.51Enemies flashed / flash
0.5%Flash assists
9.60HE damage / grenade
2.20Flashes / 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. 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 10.8473% — below the 15% mark we flag

    Aim Training →
  2. Grenades & Utility

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 2.1981 — below the 4 mark we flag

    Grenade Lineups →
Spend your practice time on Nuke

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

39% win rate across 18 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage6–13-0.038%11 Oct →
office12–90.0315%11 Oct →
office13–80.023%11 Oct →
nuke9–40.1512%11 Oct →
office13–10.0331%11 Oct →
nuke7–9-0.018%10 Oct →
inferno7–90.0712%10 Oct →
overpass1–9-0.1813%10 Oct →
mirage13–40.0120%10 Oct →
office6–130.087%10 Oct →
office13–80.1111%10 Oct →
office11–13-0.014%9 Oct →
office13–10-0.0510%9 Oct →
inferno2–9-0.098%8 Oct →
inferno9–3-0.0628%8 Oct →
overpass4–9-0.118%8 Oct →
debris4–9-0.219%8 Oct →
nuke5–90.008%8 Oct →
inferno9–50.129%8 Oct →
office13–9-0.0513%8 Oct →
nuke8–80.016%7 Oct →
inferno6–9-0.0318%7 Oct →
inferno9–40.0335%7 Oct →
inferno3–9-0.174%7 Oct →
nuke8–80.175%7 Oct →
vertigo9–40.1216%7 Oct →
nuke7–90.085%7 Oct →
inferno4–9-0.0212%7 Oct →
nuke9–30.113%7 Oct →
inferno5–9-0.047%7 Oct →
inferno9–30.0313%7 Oct →
nuke8–80.098%7 Oct →
nuke13–50.0815%7 Oct →
dust213–8-0.029%7 Oct →
nuke9–13-0.0211%7 Oct →
overpass7–130.027%7 Oct →
train13–8-0.0311%7 Oct →
train13–10.0137%7 Oct →
cache10–13-0.0411%6 Oct →
inferno11–13-0.036%6 Oct →
dust26–13-0.0112%6 Oct →
cache13–70.087%6 Oct →
dust213–7-0.035%5 Oct →
dust25–130.0524%5 Oct →
cache13–10-0.066%5 Oct →
office12–12-0.054%5 Oct →
office12–6-0.019%5 Oct →
mirage14–16-0.019%4 Oct →
office13–8-0.0310%4 Oct →
office13–100.0312%4 Oct →
office13–90.0412%4 Oct →
office12–120.0310%3 Oct →
nuke13–80.0912%3 Oct →
dust27–130.0111%3 Oct →
anubis15–150.058%3 Oct →
office13–90.0514%3 Oct →
office6–130.036%3 Oct →
office9–130.028%3 Oct →
office13–100.139%3 Oct →
office12–120.058%3 Oct →
office13–7-0.0015%3 Oct →
office13–40.0813%3 Oct →
office11–130.0416%3 Oct →
office13–80.0617%3 Oct →
nuke8–130.046%2 Oct →
nuke3–13-0.0719%2 Oct →
nuke8–130.0311%2 Oct →
mirage13–50.0815%2 Oct →
office13–70.0814%2 Oct →
dust213–50.069%1 Oct →
nuke3–130.1111%1 Oct →
cache13–90.046%1 Oct →
inferno6–20.18100%1 Oct →
nuke9–50.1110%1 Oct →
nuke13–100.037%1 Oct →
mirage13–60.0312%1 Oct →
dust210–13-0.0410%1 Oct →
inferno13–40.0117%1 Oct →
mirage13–50.0711%1 Oct →
mirage7–13-0.0012%1 Oct →
cache13–8-0.013%1 Oct →
nuke13–11-0.008%1 Oct →
dust28–3-0.0110%30 Sept →
mirage5–13-0.027%30 Sept →
inferno7–130.027%30 Sept →
mirage1–130.086%30 Sept →
dust213–90.0513%30 Sept →
dust213–70.0712%30 Sept →
mirage3–8-0.0122%30 Sept →
ancient8–130.1016%30 Sept →
anubis13–80.035%30 Sept →
mirage13–70.0712%30 Sept →
mirage7–13-0.0215%30 Sept →
anubis4–13-0.0020%30 Sept →
dust22–13-0.0210%29 Sept →
dust213–5-0.0415%29 Sept →
mirage13–6-0.0313%29 Sept →
inferno13–6-0.028%29 Sept →
dust216–13-0.048%29 Sept →
mirage13–160.0011%29 Sept →

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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