G A M E R S Y N

G A M E R S Y N — CS2 Stats

KG76561198189128774[U:1:228863046]Steam profile ↗✓ No bans

275Tracked matches59%Win rate2023Tracked since
CSDB Rating6.2 SolidAll-Rounder
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 23 Sep 2026 (yesterday). Ranks are recorded once per day this page is viewed.

No change since then — still 275 tracked matches. Play, then come back: the next observation lands here.

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. 61 days played since 30 Sep 2025. Come back after the next session and the change shows above.

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Rating over time

Premier CS Rating: 12,212 -4,791 30 Sept18 Jan · 21 days played
11,73317,003peak 17,00330 Sept18 Jan
17,003Peak Premier in tracked matches
61Days played since 2025-09-30

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Performance scores

Aim66
Positioning60
Utility58

0–100 skill scores via Leetify.

Recent form

STEADY51463Last 10051%Win rateLWLLWLWWLW

Last 10 vs previous 10: −10pp win rate · −0.01 avg rating · +0.2pp headshot accuracy · −57ms reaction

Win rate −10pp 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

  • 23 · 40% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 18%
  • Avg reaction 603ms

Last 10

  • 55 · 50% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 14%
  • Avg reaction 552ms

Last 20

  • 1181 · 55% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 14%
  • Avg reaction 580ms

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: All-RounderNo style dimension stands clear of the others in this profile.

Aim6.6
Utility5.8
Positioning6.0
Opening Duels3.8

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 84% 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

Reaction time. 596ms 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

Aim6.6
Positioning6.0
Utility5.8
Mechanics7.2
Opening Duels3.2
Win Impact7.9

Composite 6.2/10 (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 rating0.02+0.01
first ⅓ avg 0.01 → last ⅓ avg 0.02
Reaction time607ms−58ms
first ⅓ avg 664ms → last ⅓ avg 607ms
Headshot accuracy14.4%−3.7%
first ⅓ avg 18.1% → last ⅓ avg 14.4%

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

0.20Best match rating · 13–2 · office, 26 Nov
56%Best headshot accuracy · 2–13 · overpass, 28 Feb
438msFastest reaction time · 8–13 · anubis, 11 Jun
13–1Biggest win · office, 17 May

Across the last 100 tracked matches.

Highlights

5Longest win streak
46In matches decided by ≤2 rounds
3Overtime games

Map breakdown

nukeBest map · 64% over 14anubisWeakest map · 22% over 9
MapGradePlayedRecordWin rateAvg rating
nukeA149564%0.02
trainA148657%0.02
cacheA138562%0.02
dust2D93633%-0.00
anubisD92722%0.01
vertigoD93633%0.02
ancientA85363%0.01
officeA74357%0.06
overpassA74357%-0.01
mirage41325%-0.00
alpine32167%0.06
inferno21150%0.03
stronghold110100%0.07

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (22% over 9). Start with the 6 essential Anubis 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.

14.7%Headshot accuracy
34.9%Accuracy (enemy spotted)
35.6%Spray accuracy
82.5%Counter-strafing
9.7°Preaim
596msReaction time
39.4%T opening success
46.1%CT opening success
0.58Enemies flashed / flash
4.3%Flash assists
8.14HE damage / grenade
8.59Flashes / 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 14.7041% — 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 39.4333% — 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.

22% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategyAnubis grenade lineups

Recent matches

MapScoreRatingHS%Date
dust212–16-0.0013%26 Jul
nuke13–70.1225%24 Jul
office9–130.0514%13 Jul
anubis8–13-0.0519%3 Jul
nuke13–80.0217%3 Jul
anubis8–13-0.0711%11 Jun
dust213–30.028%11 Jun
ancient13–90.0416%8 Jun
vertigo5–130.0412%7 Jun
vertigo13–110.018%7 Jun
anubis10–13-0.068%27 May
stronghold13–80.0721%24 May
cache12–12-0.0614%24 May
cache13–60.1819%23 May
cache13–30.0415%20 May
cache7–130.0315%17 May
cache13–20.058%17 May
office13–10.0210%17 May
office11–130.0618%13 May
cache13–6-0.0714%12 May
cache13–10-0.0419%11 May
cache10–130.0124%11 May
alpine1–130.0916%8 May
cache13–100.0817%8 May
cache13–50.0623%8 May
alpine13–70.1016%4 May
cache5–13-0.078%4 May
cache3–13-0.0611%4 May
cache12–00.139%3 May
train13–6-0.038%28 Apr
train4–0-0.030%28 Apr
train13–80.0313%28 Apr
train13–90.0729%26 Apr
vertigo5–130.0332%12 Apr
vertigo3–130.0331%12 Apr
anubis13–30.1319%6 Apr
anubis8–130.0213%6 Apr
office13–100.0514%22 Mar
nuke13–90.0128%21 Mar
office13–100.0316%21 Mar
overpass13–11-0.037%15 Mar
anubis12–16-0.0111%12 Mar
alpine13–10-0.0217%8 Mar
mirage7–3-0.065%8 Mar
vertigo3–13-0.0130%8 Mar
dust29–13-0.0428%8 Mar
nuke13–70.1019%5 Mar
ancient13–100.0514%28 Feb
dust27–13-0.0312%28 Feb
train2–13-0.0220%28 Feb
overpass2–13-0.0856%28 Feb
anubis12–120.0315%28 Feb
overpass3–130.0112%28 Feb
overpass13–50.0622%24 Jan
dust216–130.0019%23 Jan
ancient13–2-0.0330%18 Jan
dust29–13-0.0118%18 Jan
train5–13-0.0622%8 Jan
train13–90.038%8 Jan
overpass13–80.0522%7 Jan
train13–50.119%6 Jan
train6–130.0717%6 Jan
mirage8–13-0.0122%30 Dec
nuke13–110.0920%26 Dec
nuke5–13-0.0414%26 Dec
dust213–10.0529%22 Dec
vertigo9–13-0.0414%21 Dec
vertigo13–70.0319%17 Dec
nuke13–80.0218%16 Dec
train8–13-0.0114%15 Dec
mirage5–130.0132%15 Dec
ancient9–130.059%14 Dec
nuke10–13-0.059%10 Dec
train11–130.0117%8 Dec
train13–110.0431%30 Nov
ancient9–13-0.0624%27 Nov
office10–13-0.0217%26 Nov
office13–20.2035%26 Nov
mirage10–130.0519%25 Nov
train13–80.0419%20 Nov
overpass13–6-0.0412%20 Nov
nuke13–50.0419%15 Nov
ancient13–60.0211%15 Nov
nuke11–13-0.0134%13 Nov
nuke13–50.018%13 Nov
overpass4–13-0.0311%13 Nov
dust211–13-0.017%12 Nov
inferno13–60.0916%9 Nov
train6–130.0013%9 Nov
nuke10–13-0.0330%8 Nov
nuke3–130.0418%4 Nov
inferno3–13-0.0325%4 Nov
dust27–13-0.0127%2 Nov
vertigo11–130.0115%27 Oct
vertigo13–20.0419%27 Oct
anubis12–120.0621%15 Oct
anubis13–40.0111%15 Oct
ancient11–130.0012%1 Oct
nuke13–3-0.0212%30 Sept
ancient13–10.0014%30 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 →