Kepler

Kepler — CS2 Stats

US76561198086698111[U:1:126432383]Steam profile ↗

1,382Tracked matches54%Win rate2021Tracked since
3,413Hours in CS25Hrs last 2 wks
CSDB Rating5.9 SolidAggressive Rifler
Ladder ranks via Leetify

Performance scores

Aim75
Positioning52
Utility41

0–100 skill scores via Leetify.

Recent form

STEADY583111Last 10058%Win rateLTWLLWWLLW

Last 10 vs previous 10: -20pp win rate · -0.02 avg rating

Player DNA

Primary style: Aggressive RiflerTakes opening fights often, backed by a strong aim profile.

Aim7.5
Aggression7.9
Utility4.1
Positioning5.2
Opening Duels5.2

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.

Your pro match

ropz

Plays most like ropz 90% playstyle similarity

Most alike: opening-duel success, opening-fight frequency.

Where you differ: 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

Strengths

CT openings. 64% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

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

T-side openings. Opening success drops from 64% on CT to 37% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 577ms 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

Aim7.5
Positioning5.2
Utility4.1
Mechanics5.8
Opening Duels5.2
Win Impact6.2

Composite 5.9/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.00+0.00
first ⅓ avg 0.00 → last ⅓ avg 0.00
Reaction time576ms−35ms
first ⅓ avg 612ms → last ⅓ avg 576ms
Headshot accuracy14.5%−3.0%
first ⅓ avg 17.6% → last ⅓ avg 14.5%

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

0.11Best rating — nuke 12–12
131Biggest win — dust2
10Longest win streak
95In matches decided by ≤2 rounds

Map breakdown

cacheBest map · 67% over 12trainWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
dust2A32201263%0.02
infernoB179853%0.01
mirageA1710759%0.02
cacheS128467%-0.00
trainD61517%-0.01
anubisS64267%-0.02
vertigoA53260%0.01
ancient32167%-0.01
nuke21150%0.06

Across the last 100 tracked matches.

Lifetime stats

168,246Lifetime kills
0.99K/D
7,919Matches
20.2%Match win rate
38.6%Headshot %
17.3%Shot accuracy · Top 25% of tracked players
7,294MVPs
2,217Hours (in match)
1,943Bombs planted
641Bombs defused

Most-used weapons

AK-4732,090
AWP9,785
P2506,212
SSG 085,246
AUG4,136

Lifetime map wins

8,726dust2
5,864inferno
1,321nuke
1,179train
997vertigo
696cbble
95office
94lake

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

Faceit stats

Combat

82Matches
51%Win rate
0.91Avg K/D
ADR
32%Headshot %

Clutches & streaks

1v1 clutch win
1v2 clutch win
6Longest win streak

Recent Faceit resultsWWWLL

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.

14.7%Headshot accuracy
39.8%Accuracy (enemy spotted)
43.7%Spray accuracy
76.0%Counter-strafing
9.8°Preaim
577msReaction time
37.5%T opening success
63.8%CT opening success
0.51Enemies flashed / flash
6.7%Flash assists
13.39HE damage / grenade
3.24Flashes / 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 14.72% — 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 3.2382 — below the 4 mark we flag

    Grenade Lineups
  3. 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 37.4524% — 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.

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy

Recent matches

MapScoreRatingHS%Date
train7–13-0.0719%28 Aug
train12–12-0.0013%28 Aug
cache13–2-0.0613%28 Aug
inferno8–130.0316%27 Aug
anubis3–13-0.069%26 Aug
dust213–50.0511%26 Aug
inferno13–8-0.0120%25 Aug
mirage7–130.0213%25 Aug
dust210–130.047%25 Aug
mirage13–110.0218%24 Aug
inferno9–130.0229%24 Aug
dust26–4-0.0115%24 Aug
inferno9–130.0419%23 Aug
ancient6–13-0.0513%23 Aug
dust213–80.0112%23 Aug
mirage13–50.0310%22 Aug
mirage13–2-0.0315%22 Aug
dust211–13-0.0418%22 Aug
mirage13–30.0819%21 Aug
dust213–40.0610%21 Aug
mirage11–13-0.048%20 Aug
mirage7–130.0411%20 Aug
inferno13–90.0114%20 Aug
cache13–20.0117%20 Aug
cache13–60.0716%19 Aug
inferno13–90.0012%19 Aug
dust212–120.0315%18 Aug
dust213–1-0.0214%18 Aug
dust211–13-0.0214%18 Aug
cache9–13-0.0220%18 Aug
vertigo13–6-0.0016%18 Aug
nuke13–100.0119%18 Aug
mirage12–12-0.016%17 Aug
dust213–110.0116%17 Aug
dust25–130.0817%17 Aug
inferno13–70.0116%17 Aug
dust213–100.0713%16 Aug
dust213–20.1018%16 Aug
train13–70.0611%15 Aug
dust213–60.1018%15 Aug
inferno9–13-0.0212%13 Aug
dust29–13-0.0112%11 Aug
dust213–6-0.0413%10 Aug
dust213–50.019%9 Aug
anubis9–13-0.0613%8 Aug
cache13–7-0.0215%8 Aug
inferno9–13-0.026%6 Aug
mirage13–80.0414%3 Aug
vertigo13–50.0112%3 Aug
dust213–80.0812%2 Aug
train7–13-0.0116%2 Aug
vertigo13–60.0710%2 Aug
cache13–100.0215%2 Aug
mirage10–13-0.0613%2 Aug
dust213–110.0516%2 Aug
inferno13–11-0.0223%1 Aug
mirage13–20.0621%31 Jul
inferno13–30.0523%31 Jul
dust212–120.0117%31 Jul
cache10–13-0.0017%30 Jul
cache8–130.0021%30 Jul
mirage13–100.0919%30 Jul
dust22–00.0325%30 Jul
train12–12-0.0219%28 Jul
dust213–5-0.0521%28 Jul
mirage13–30.055%28 Jul
ancient13–100.0329%28 Jul
anubis13–110.0324%28 Jul
cache13–2-0.0818%27 Jul
dust213–20.0530%27 Jul
anubis8–1-0.0719%26 Jul
inferno13–110.0125%26 Jul
mirage13–8-0.0123%26 Jul
cache13–40.0426%26 Jul
dust29–130.0613%26 Jul
train12–12-0.0013%25 Jul
dust213–90.0133%25 Jul
inferno7–13-0.0222%25 Jul
anubis13–11-0.0112%24 Jul
mirage13–90.0217%24 Jul
vertigo9–13-0.0312%24 Jul
mirage6–130.0225%23 Jul
dust213–4-0.0514%23 Jul
dust212–12-0.0417%23 Jul
dust211–13-0.0120%20 Jul
dust213–6-0.0210%20 Jul
inferno12–12-0.0015%19 Jul
dust213–6-0.0017%19 Jul
dust24–13-0.0418%19 Jul
cache13–90.0616%19 Jul
inferno13–40.028%19 Jul
vertigo11–130.0212%17 Jul
ancient13–4-0.0318%17 Jul
nuke12–120.1121%17 Jul
dust28–13-0.0111%17 Jul
cache12–12-0.0218%16 Jul
inferno13–70.0515%16 Jul
mirage8–130.0214%16 Jul
inferno12–12-0.0411%16 Jul
anubis13–100.0413%15 Jul

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches10-Win Streak
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →