GONGON

GONGON — CS2 Stats

76561197988826688[U:1:28560960]Steam profile ↗✓ No bans

206Tracked matches56%Win rate2020Tracked since
CSDB Rating4.3 DevelopingSupport
WingmanMaster Guardian Elite
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 13,495 +458 24 Feb – 19 Jan · 17 days played
6,55514,774peak 14,77424 Feb19 Jan
14,774Peak Premier in tracked matches
35Days played since 2024-02-24

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

Performance scores

Aim31
Positioning42
Utility60

0–100 skill scores via Leetify.

Recent form

STEADY49–44–7Last 10049%Win rateWWTLTWWLTW

Last 10 vs previous 10: −10pp win rate · −0.01 avg rating · +5.0pp headshot accuracy · −105ms 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

  • 2–1–2 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 17%
  • Avg reaction 613ms

Last 10

  • 5–2–3 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 15%
  • Avg reaction 621ms

Last 20

  • 11–6–3 · 55% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 13%
  • Avg reaction 673ms

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: Support — Utility contribution stands above the rest of this profile (+2.4 against its own average).

Aim3.1
Utility6.0
Positioning4.2
Opening Duels0.7

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

sh1ro

Plays most like sh1ro 57% 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. 681ms 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

Aim3.1
Positioning4.2
Utility6.0
Mechanics5.9
Opening Duels1.0
Win Impact6.9

Composite 4.3/10 (Developing), 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 rating-0.01−0.01
first ⅓ avg 0.00 → last ⅓ avg -0.01
Reaction time687ms−4ms
first ⅓ avg 691ms → last ⅓ avg 687ms
Headshot accuracy13.8%+0.9%
first ⅓ avg 12.9% → last ⅓ avg 13.8%

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

0.10Best match rating · 9–13 · mirage, 9 Nov →
33%Best headshot accuracy · 13–4 · anubis, 24 Feb →
500msFastest reaction time · 13–1 · vertigo, 8 May →
13–1Biggest win · vertigo, 8 May →

Across the last 100 tracked matches.

Highlights

5Longest win streak
W2Current streak
8–11In matches decided by ≤2 rounds
10Overtime games

Map breakdown

infernoBest map · 71% over 17dust2Weakest map · 21% over 19
MapGradePlayedRecordWin rateAvg rating
dust2D194–1521%-0.01
mirageB1910–953%0.00
infernoS1712–571%-0.00
nukeA138–562%-0.00
ancientA127–558%-0.02
overpassC73–443%-0.01
anubisB63–350%0.01
cache—20–20%-0.04
train—21–150%0.01
vertigo—21–150%0.04
office—10–10%-0.05

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (21% over 19). Start with the 6 essential Dust 2 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.

13.4%Headshot accuracy
27.7%Accuracy (enemy spotted)
28.5%Spray accuracy
76.7%Counter-strafing
11.2°Preaim
681msReaction time
24.8%T opening success
38.1%CT opening success
0.61Enemies flashed / flash
3.8%Flash assists
6.39HE damage / grenade
16.00Flashes / 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 13.4106% — 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 24.7955% — below the 40% mark we flag

Spend your practice time on Dust 2

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

21% win rate across 19 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno13–10-0.0617%31 Aug →
nuke13–110.0510%31 Aug →
nuke15–15-0.0529%31 Aug →
dust28–13-0.0512%30 Aug →
cache15–15-0.0315%30 Aug →
mirage13–60.0416%30 Aug →
mirage13–9-0.009%3 Jun →
inferno13–160.0310%3 Jun →
dust215–15-0.0219%2 Jun →
anubis13–11-0.0317%2 Jun →
nuke13–30.0316%5 May →
cache9–13-0.0516%5 May →
nuke11–13-0.0211%22 Feb →
inferno13–2-0.0017%22 Feb →
inferno13–7-0.003%21 Feb →
dust213–4-0.045%21 Feb →
overpass13–30.043%19 Feb →
anubis11–130.0410%19 Feb →
dust25–13-0.0114%19 Feb →
ancient13–50.039%19 Feb →
inferno11–130.0614%14 Feb →
mirage11–130.0517%14 Feb →
ancient6–13-0.096%19 Jan →
dust213–10-0.0315%19 Jan →
nuke13–11-0.0213%16 Jan →
ancient14–160.0311%16 Jan →
inferno8–30.0212%16 Jan →
mirage13–7-0.0115%16 Jan →
dust24–13-0.0322%16 Jan →
dust29–9-0.0310%14 Jan →
ancient8–13-0.0624%14 Jan →
anubis11–13-0.0111%14 Jan →
mirage7–13-0.0330%8 Jan →
ancient13–10-0.0310%8 Jan →
nuke9–13-0.059%8 Jan →
mirage13–70.0214%1 Jan →
inferno13–11-0.0212%1 Jan →
dust213–80.0429%1 Jan →
overpass10–130.0318%19 Dec →
dust29–130.0416%19 Dec →
mirage5–13-0.107%19 Dec →
nuke16–140.0314%19 Dec →
dust26–13-0.0013%11 Dec →
inferno8–13-0.0316%11 Dec →
ancient9–13-0.0417%11 Dec →
nuke6–13-0.0116%7 Dec →
dust213–80.0720%2 Dec →
mirage6–13-0.037%2 Dec →
overpass13–60.0117%2 Dec →
inferno15–15-0.056%11 Nov →
mirage9–130.1013%9 Nov →
nuke5–13-0.0710%9 Nov →
inferno13–8-0.023%9 Nov →
dust29–130.0124%4 Nov →
mirage13–70.0020%4 Nov →
inferno13–11-0.0013%4 Nov →
inferno13–90.0616%12 Oct →
ancient13–40.019%12 Oct →
dust211–13-0.0311%12 Oct →
mirage13–6-0.096%12 Oct →
ancient8–130.0518%12 Oct →
office12–12-0.057%7 Oct →
overpass10–13-0.0015%30 Sept →
ancient13–80.0220%30 Sept →
inferno13–110.0114%26 Sept →
mirage4–13-0.029%26 Sept →
overpass13–80.0010%26 Sept →
dust215–150.0210%26 Sept →
nuke13–10-0.0020%26 Sept →
overpass5–13-0.0510%26 Sept →
inferno13–70.007%24 Sept →
mirage13–20.0014%24 Sept →
ancient13–9-0.045%24 Sept →
ancient13–7-0.0211%19 Sept →
overpass9–13-0.0910%19 Sept →
train13–50.0316%19 Sept →
mirage14–160.0412%19 Sept →
inferno13–60.0111%19 Sept →
nuke13–110.0314%3 Sept →
dust27–130.0221%3 Sept →
mirage13–5-0.0211%31 May →
vertigo11–130.0015%31 May →
train10–13-0.009%31 May →
dust211–13-0.0412%31 May →
anubis13–80.0213%8 May →
vertigo13–10.0912%8 May →
ancient13–7-0.069%8 May →
inferno13–60.0217%22 Apr →
mirage13–80.068%22 Apr →
anubis3–130.0221%22 Apr →
nuke9–20.023%22 Apr →
dust24–13-0.0117%21 Apr →
mirage10–130.0814%1 Nov →
dust215–150.0113%1 Nov →
mirage13–60.0513%1 Nov →
inferno7–13-0.058%30 Aug →
dust23–13-0.0311%30 Aug →
mirage7–13-0.0813%30 Aug →
nuke13–60.0512%24 Feb →
anubis13–40.0233%24 Feb →

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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