KIAT.ゴールドパンツ

KIAT.ゴールドパンツ — CS2 Stats

SG76561197998368302[U:1:38102574]Steam profile ↗✓ No bans

1,085Tracked matches45%Win rate2020Tracked since
CSDB Rating5.7 SolidSupport
FaceitLevel 7 · 1,541 ELOTop 42.3% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGKIAT.ゴールドパンツFACEITLevel 7 · 1,541 ELOSTANDINGTop 42.3% of rankedcsdb.gg/stats

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Performance scores

Aim86
Positioning50
Utility54

0–100 skill scores via Leetify.

Recent form

COLD47–52–1Last 10047%Win rateWLLLWLWLLL

Last 10 vs previous 10: −40pp win rate · −0.03 avg rating · −0.6pp headshot accuracy · +27ms reaction

Win rate down 40pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 2–3 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 20%
  • Avg reaction 591ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 18%
  • Avg reaction 567ms

Last 20

  • 10–9–1 · 50% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 18%
  • Avg reaction 554ms

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 (+1.4 against its own average).

Aim8.6
Utility5.4
Positioning5.0
Opening Duels2.9
Clutch2.8

Sharp aimerStrong CT-side opener

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

device

Plays most like device 92% playstyle similarity

Most alike: aim profile, utility contribution.

Where you differ: lower positioning profile; lower opening-duel success.

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

Aim. Aim score of 86 — the mechanical foundation is a clear strength.

Areas to improve

Positioning. Positioning trails aim by 36 points — deaths here waste a strong aim profile.

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 54% on CT to 26% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 567ms 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

Aim8.6
Positioning5.0
Utility5.4
Mechanics6.3
Opening Duels3.0
Win Impact3.3

Composite 5.7/10 (Solid), 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+0.01
first ⅓ avg -0.01 → last ⅓ avg 0.00
Reaction time588ms−58ms
first ⅓ avg 646ms → last ⅓ avg 588ms
Headshot accuracy18.9%−0.2%
first ⅓ avg 19.1% → last ⅓ avg 18.9%

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

0.09Best match rating · 9–13 · ancient, 13 Jul →
37%Best headshot accuracy · 13–1 · nuke, 9 Jul →
422msFastest reaction time · 13–4 · nuke, 20 Aug →
13–1Biggest win · nuke, 9 Jul →

Across the last 100 tracked matches.

Highlights

5Longest win streak
5–12In matches decided by ≤2 rounds
14Overtime games

Map breakdown

nukeBest map · 65% over 23cacheWeakest map · 13% over 8
MapGradePlayedRecordWin rateAvg rating
infernoA2917–1259%-0.01
ancientC249–1538%0.00
nukeS2315–865%0.00
anubisD165–1131%-0.00
cacheD81–713%-0.03

Across the last 100 tracked matches.

Faceit stats

Combat

735Matches
50%Win rate
1.05Avg K/D
75.5ADR
44%Headshot %

Clutches & streaks

34%1v1 clutch win
22%1v2 clutch win
8Longest win streak

Recent Faceit resultsLLWLW

MapMatchesWin rateAvg K/DAvg kills
Inferno15052%1.0314.7
Ancient14647%0.9915.5
Nuke9552%1.0015.1
Anubis9450%1.1216.0
Overpass2733%0.8613.5
Dust21362%0.9415.5
Cache1127%0.7613.4
Train850%0.6510.9

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.

18.8%Headshot accuracy
40.6%Accuracy (enemy spotted)
45.9%Spray accuracy
78.3%Counter-strafing
8.8°Preaim
567msReaction time
26.0%T opening success
54.3%CT opening success
0.62Enemies flashed / flash
9.2%Flash assists
7.93HE damage / grenade
5.82Flashes / 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. 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 26% — below the 40% mark we flag

Spend your practice time on Cache

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

13% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
inferno13–9-0.0217%28 Aug →
anubis10–13-0.0917%28 Aug →
inferno5–13-0.0719%28 Aug →
inferno8–13-0.0224%25 Aug →
inferno16–120.0421%25 Aug →
inferno20–22-0.049%24 Aug →
anubis13–110.0314%24 Aug →
nuke12–16-0.0019%22 Aug →
ancient5–13-0.0420%22 Aug →
anubis5–130.0117%22 Aug →
nuke13–7-0.067%22 Aug →
inferno6–130.0226%22 Aug →
ancient13–60.0410%20 Aug →
inferno10–3-0.0215%20 Aug →
anubis13–30.0532%20 Aug →
nuke13–40.0315%20 Aug →
nuke13–9-0.0229%19 Aug →
anubis15–150.0217%19 Aug →
nuke8–130.0113%15 Aug →
inferno13–80.0519%9 Aug →
inferno6–130.0425%8 Aug →
ancient13–90.0526%30 Jul →
anubis10–130.0735%29 Jul →
cache9–13-0.0220%29 Jul →
ancient13–30.0713%29 Jul →
ancient7–13-0.0721%17 Jul →
inferno13–10-0.018%17 Jul →
ancient13–16-0.0322%15 Jul →
anubis11–13-0.0724%15 Jul →
ancient9–130.0918%13 Jul →
inferno13–70.0221%13 Jul →
nuke8–13-0.0121%13 Jul →
ancient10–13-0.0412%10 Jul →
nuke13–50.0421%10 Jul →
nuke13–9-0.0127%10 Jul →
inferno13–10-0.0515%9 Jul →
nuke13–10.0837%9 Jul →
nuke11–13-0.0413%4 Jul →
anubis4–13-0.0317%4 Jul →
inferno10–13-0.0122%4 Jul →
nuke10–130.0216%3 Jul →
inferno10–13-0.0328%3 Jul →
ancient6–13-0.048%2 Jul →
ancient8–13-0.0219%2 Jul →
inferno13–80.0427%2 Jul →
nuke13–40.0013%1 Jul →
ancient13–11-0.0120%1 Jul →
nuke13–60.0411%1 Jul →
ancient12–160.0114%28 Jun →
anubis9–130.0330%27 Jun →
ancient16–13-0.0334%27 Jun →
cache13–11-0.0222%27 Jun →
anubis11–13-0.0225%27 Jun →
inferno13–9-0.0028%26 Jun →
inferno13–70.0210%26 Jun →
anubis13–50.0017%26 Jun →
cache10–13-0.0013%26 Jun →
ancient11–130.0619%26 Jun →
inferno9–13-0.0318%26 Jun →
inferno13–50.0235%24 Jun →
inferno9–13-0.066%24 Jun →
anubis6–13-0.0518%24 Jun →
cache13–16-0.0732%23 Jun →
inferno13–20.0112%23 Jun →
ancient13–7-0.0111%23 Jun →
anubis8–13-0.0413%23 Jun →
nuke13–9-0.0211%20 Jun →
inferno9–13-0.0122%20 Jun →
nuke10–13-0.0212%20 Jun →
ancient11–130.0214%20 Jun →
nuke16–12-0.0112%19 Jun →
ancient13–60.0314%19 Jun →
ancient7–130.0233%19 Jun →
nuke13–100.0116%19 Jun →
ancient7–13-0.0120%18 Jun →
cache6–13-0.0727%16 Jun →
nuke11–13-0.0431%16 Jun →
inferno13–8-0.0215%16 Jun →
anubis13–60.0316%14 Jun →
nuke13–60.0028%14 Jun →
ancient9–13-0.0216%14 Jun →
inferno17–19-0.0114%13 Jun →
inferno13–11-0.0613%13 Jun →
ancient13–50.0413%13 Jun →
cache14–160.0113%12 Jun →
nuke13–100.0122%12 Jun →
inferno13–80.0422%6 Jun →
inferno16–13-0.0116%4 Jun →
anubis11–13-0.0121%30 May →
anubis16–130.0422%17 May →
nuke10–13-0.0516%17 May →
ancient11–13-0.0221%15 May →
nuke13–30.0811%15 May →
inferno3–13-0.0220%15 May →
ancient11–130.0021%6 May →
cache8–13-0.0423%6 May →
cache6–13-0.0029%5 May →
nuke16–12-0.0315%5 May →
inferno13–11-0.0517%2 May →
ancient13–8-0.0527%2 May →

Match data via Leetify.

Recent teammates

Milestones

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

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