Handsome

Handsome — CS2 Stats

76561199189907440[U:1:1229641712]Steam profile ↗✓ No bans

264Tracked matches41%Win rate2024Tracked since
CSDB Rating3.7 Learning
FaceitLevel 3 · 899 ELOTop 90.6% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGHandsomeFACEITLevel 3 · 899 ELOSTANDINGTop 90.6% of rankedcsdb.gg/stats

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Performance scores

Aim56
Positioning43
Utility37

0–100 skill scores via Leetify.

Recent form

COLD43534Last 10043%Win rateWWTLLWLLLL

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

Player DNA

Aim5.6
Aggression4.4
Utility3.7
Positioning4.3
Opening Duels0.5
Clutch3.6

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

NiKo

Plays most like NiKo 80% playstyle similarity

Most alike: opening-fight frequency, 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

T-side openings. Opening success drops from 42% on CT to 23% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 619ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 69% 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

Aim5.6
Positioning4.3
Utility3.7
Mechanics4.3
Opening Duels1.4
Win Impact2.1

Composite 3.7/10 (Learning), 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+0.02
first ⅓ avg -0.01 → last ⅓ avg 0.00
Reaction time619ms−24ms
first ⅓ avg 643ms → last ⅓ avg 619ms
Headshot accuracy12.3%+2.1%
first ⅓ avg 10.2% → last ⅓ avg 12.3%

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

0.12Best rating — anubis 13–0
130Biggest win — anubis
3Longest win streak
W2Current streak
812In matches decided by ≤2 rounds
12Overtime games

Map breakdown

nukeBest map · 50% over 20anubisWeakest map · 30% over 10
MapGradePlayedRecordWin rateAvg rating
mirageC28101836%-0.01
nukeB20101050%-0.02
infernoB189950%-0.00
ancientC146843%-0.01
anubisD103730%-0.01
train43175%-0.00
dust242250%0.01
overpass1010%0.00
cache1010%-0.07

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (30% over 10). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

33Matches
33%Win rate
0.80Avg K/D
65.1ADR
35%Headshot %

Clutches & streaks

38%1v1 clutch win
21%1v2 clutch win
2Longest win streak

Recent Faceit resultsLWLWL

MapMatchesWin rateAvg K/DAvg kills
Ancient729%0.6411.6
Anubis729%0.7810.0
Nuke633%0.8413.0
Mirage633%0.9213.7
Inferno650%0.8511.5
Dust210%0.8815.0

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.

12.0%Headshot accuracy
38.4%Accuracy (enemy spotted)
40.5%Spray accuracy
69.1%Counter-strafing
11.0°Preaim
619msReaction time
22.8%T opening success
41.6%CT opening success
0.51Enemies flashed / flash
3.3%Flash assists
4.72HE damage / grenade
10.50Flashes / 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 12.043% — below the 15% mark we flag

    Aim Training
  2. 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 22.7752% — below the 40% mark we flag

Spend your practice time on Anubis

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

30% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategyAnubis grenade lineups

Recent matches

MapScoreRatingHS%Date
train13–7-0.0910%28 Aug
train13–90.0415%21 Aug
inferno12–120.0013%29 Jul
dust210–130.0422%26 Jul
mirage10–130.0011%20 Jul
anubis13–00.1220%16 Jul
mirage13–16-0.0113%16 Jul
ancient6–130.0513%12 Jul
nuke11–13-0.068%12 Jul
ancient12–16-0.0210%11 Jul
nuke13–100.057%3 Jul
inferno16–140.0513%2 Jul
ancient13–3-0.0411%2 Jul
mirage9–13-0.009%2 Jul
mirage5–13-0.0914%1 Jul
nuke8–13-0.0515%1 Jul
inferno8–10.0912%1 Jul
dust213–6-0.0216%29 Jun
anubis11–13-0.090%29 Jun
anubis11–130.0010%28 Jun
mirage6–110.0130%27 Jun
anubis2–13-0.0910%27 Jun
inferno8–10.0414%27 Jun
inferno8–13-0.0416%27 Jun
nuke13–110.049%27 Jun
nuke11–13-0.019%26 Jun
mirage13–110.064%26 Jun
nuke13–11-0.0114%24 Jun
nuke11–13-0.0117%24 Jun
ancient7–130.0511%24 Jun
nuke13–50.0211%23 Jun
mirage5–130.0113%20 Jun
overpass10–130.0011%19 Jun
ancient13–8-0.0115%19 Jun
anubis13–90.0314%19 Jun
ancient7–130.0613%19 Jun
inferno16–130.0011%19 Jun
mirage13–70.0610%19 Jun
train11–13-0.0110%14 Jun
inferno7–130.0214%14 Jun
inferno13–100.008%13 Jun
nuke11–13-0.069%13 Jun
mirage13–5-0.0310%13 Jun
ancient12–16-0.073%13 Jun
mirage9–13-0.0615%9 Jun
nuke5–13-0.073%7 Jun
inferno11–130.0114%6 Jun
mirage9–13-0.0617%6 Jun
ancient13–5-0.042%6 Jun
ancient12–16-0.0411%2 Jun
mirage13–80.0015%2 Jun
ancient6–13-0.026%31 May
mirage4–13-0.085%31 May
mirage8–130.037%30 May
mirage9–13-0.0816%30 May
nuke16–14-0.016%30 May
mirage13–9-0.009%30 May
mirage8–13-0.0018%30 May
nuke14–16-0.036%28 May
mirage7–13-0.0414%25 May
train6–10.0422%25 May
anubis11–13-0.0210%21 May
nuke13–10-0.0412%21 May
anubis11–13-0.0312%20 May
inferno13–11-0.0111%17 May
inferno4–130.019%16 May
nuke13–70.0211%11 May
inferno6–13-0.0715%10 May
inferno13–7-0.0010%10 May
ancient13–11-0.069%8 May
anubis9–13-0.042%7 May
ancient13–100.0016%6 May
cache5–13-0.0710%3 May
nuke16–130.0511%3 May
ancient13–80.0012%1 May
mirage7–13-0.067%1 May
nuke12–12-0.0320%29 Apr
inferno11–13-0.049%28 Apr
inferno15–150.0010%28 Apr
ancient9–130.0310%28 Apr
mirage13–70.044%28 Apr
inferno13–9-0.069%28 Apr
inferno13–9-0.033%28 Apr
mirage6–13-0.0114%28 Apr
anubis2–13-0.0310%25 Apr
mirage13–7-0.035%19 Apr
mirage16–140.0810%19 Apr
inferno15–15-0.0011%12 Apr
mirage13–70.0113%12 Apr
nuke13–10-0.005%10 Apr
mirage4–13-0.0210%31 Mar
nuke13–9-0.0312%30 Mar
mirage5–13-0.0212%30 Mar
nuke5–130.0122%30 Mar
dust213–10-0.0011%30 Mar
nuke7–13-0.102%30 Mar
dust28–130.019%30 Mar
mirage13–60.0214%28 Mar
mirage8–13-0.0313%20 Mar
anubis13–90.018%16 Mar

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 →