kites — CS2 Stats

76561198256375455[U:1:296109727]

702Tracked matches50%Win rate2022Tracked since
CSDB Rating4.6 Developing
Premier CS Rating12,195Blue band · top ~43.3% of ranked players (population est.)
CSDB Leaderboard#18959 of 27142 tracked
Ladder ranks via Leetify

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CSDB.GGkitesPREMIER12,195 · Blue bandcsdb.gg/stats

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Performance scores

Aim50
Positioning63
Utility14

0–100 skill scores via Leetify.

Recent form

COLD50455Last 10050%Win rateLLLLLWWLTW

Last 10 vs previous 10: -40pp win rate · +0.01 avg rating

Player DNA

Aim5.0
Aggression10.0
Utility1.4
Positioning6.3
Opening Duels5.7

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

ropz

Plays most like ropz 76% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution; 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

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

Reaction time. 630ms 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

Aim5.0
Positioning6.3
Utility1.4
Mechanics5.2
Opening Duels5.7
Win Impact5.0

Composite 4.6/10 (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 rating0.00+0.03
first ⅓ avg -0.02 → last ⅓ avg 0.00
Reaction time636ms−43ms
first ⅓ avg 679ms → last ⅓ avg 636ms
Headshot accuracy15.1%−0.3%
first ⅓ avg 15.4% → last ⅓ avg 15.1%

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.

Highlights

0.17Best rating — anubis 6–13
131Biggest win — ancient
5Longest win streak
L5Current streak
49In matches decided by ≤2 rounds
4Overtime games

Map breakdown

cacheBest map · 71% over 7ancientWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
mirageC1771041%-0.02
nukeB178947%-0.02
dust2B179853%-0.01
infernoB147750%-0.01
cacheS75271%-0.00
ancientD72529%-0.01
anubisA53260%0.00
vertigoA53260%-0.00
office42250%-0.02
train31233%-0.00
overpass330100%0.00
italy1010%-0.03

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

15.0%Headshot accuracy
33.1%Accuracy (enemy spotted)
38.3%Spray accuracy
73.5%Counter-strafing
11.4°Preaim
630msReaction time
56.2%T opening success
49.5%CT opening success
0.32Enemies flashed / flash
1.9%Flash assists
5.18HE damage / grenade
2.79Flashes / 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 0.3246 — below the 0.5 mark we flag

    Grenade Lineups
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.

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategyAncient grenade lineups

Recent matches

MapScoreRatingHS%Date
anubis6–130.1719%25 Aug
mirage7–130.0123%18 Aug
inferno2–130.0324%18 Aug
vertigo8–13-0.0018%17 Aug
mirage8–13-0.0113%17 Aug
nuke13–100.0610%17 Aug
inferno13–9-0.0111%15 Aug
train4–130.0017%15 Aug
nuke12–120.0718%9 Aug
mirage13–7-0.0317%5 Aug
inferno13–9-0.0110%5 Aug
mirage9–10.087%5 Aug
train13–100.0313%31 Jul
cache5–120.0424%31 Jul
nuke13–7-0.026%29 Jul
dust213–50.0418%29 Jul
dust29–00.114%29 Jul
mirage10–13-0.0313%26 Jul
nuke4–130.0028%26 Jul
vertigo13–9-0.0111%15 Jul
mirage12–12-0.0519%15 Jul
dust26–13-0.083%10 Jul
office8–130.0129%8 Jul
nuke13–10-0.0619%6 Jul
dust213–8-0.0113%6 Jul
nuke8–13-0.059%5 Jul
ancient11–13-0.049%5 Jul
overpass11–10.0213%5 Jul
mirage1–10-0.0612%5 Jul
cache13–4-0.0918%2 Jul
nuke13–11-0.0217%2 Jul
office13–110.0320%28 Jun
inferno13–7-0.0015%28 Jun
train0–7-0.040%26 Jun
office13–10-0.0133%26 Jun
dust213–50.0226%26 Jun
nuke13–2-0.0116%26 Jun
nuke13–7-0.0215%26 Jun
anubis13–10-0.0214%15 Jun
ancient14–16-0.0418%15 Jun
dust28–13-0.0413%15 Jun
nuke13–6-0.0117%15 Jun
ancient10–13-0.0512%10 Jun
anubis11–13-0.0616%8 Jun
dust213–6-0.0317%5 Jun
inferno6–13-0.0314%3 Jun
vertigo13–70.0311%3 Jun
office8–13-0.0925%3 Jun
nuke4–11-0.0323%2 Jun
mirage2–00.000%2 Jun
inferno13–60.029%31 May
mirage13–3-0.039%31 May
vertigo13–60.038%31 May
nuke8–130.0319%28 May
inferno16–130.0216%28 May
vertigo9–13-0.0511%24 May
cache6–13-0.0819%24 May
overpass13–11-0.0012%24 May
dust210–13-0.0410%24 May
ancient13–20.024%24 May
nuke14–160.0010%24 May
dust211–13-0.0113%24 May
inferno5–130.0014%24 May
italy12–12-0.0313%22 May
ancient12–12-0.0016%22 May
cache13–80.0217%22 May
inferno10–130.0117%22 May
cache13–10-0.0017%22 May
cache13–70.0214%22 May
mirage13–7-0.0014%19 May
inferno11–13-0.0719%19 May
mirage10–13-0.0214%17 May
dust215–15-0.0215%17 May
dust27–13-0.029%17 May
dust213–80.028%16 May
mirage13–30.0621%16 May
ancient13–10.1132%13 May
mirage13–6-0.059%13 May
dust213–10-0.045%10 May
mirage8–13-0.0614%10 May
dust213–40.1323%10 May
mirage9–13-0.0122%9 May
inferno11–13-0.028%9 May
overpass13–7-0.018%9 May
ancient9–13-0.0614%9 May
nuke13–5-0.0126%4 May
nuke10–13-0.0816%4 May
dust211–13-0.0722%4 May
nuke5–13-0.1217%2 May
dust210–13-0.033%2 May
nuke10–13-0.1017%2 May
mirage10–13-0.0316%2 May
inferno13–8-0.0621%2 May
mirage8–13-0.0416%2 May
cache13–90.0717%1 May
inferno13–20.0124%25 Apr
dust213–7-0.0813%25 Apr
anubis13–5-0.079%25 Apr
anubis13–8-0.0114%25 Apr
inferno11–13-0.0810%23 Apr

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 →