JKSPORTSROCKET

JKSPORTSROCKET — CS2 Stats

DE76561197976519337[U:1:16253609]Steam profile ↗VAC banned

578Tracked matches40%Win rate2021Tracked since
3,527Hours in CS12Hrs last 2 wks
CSDB Rating4.6 DevelopingClutch Specialist
Premier CS Rating4,660Grey band · top ~80.2% of ranked players (population est.)
WingmanDistinguished Master Guardian
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 2 Nov 2026 (2 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 4,660 -2,014 4 Aug – 2 Nov · 9 days played
4,6607,817peak 7,8174 Aug2 Nov
8,184Peak Premier in tracked matches
21Days played since 2026-08-04

Premier CS Rating

  • 3,157 below peak (7,817)
  • -2,014 over 90 days
  • Next: Light Blue band at 5,000 — 340 to go
  • Reached: Light Blue band

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

How this compares with the same rank

Median values for Grey band among CSDB-tracked players (n=3,645), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerGrey band medianLight Blue band medianvs Light Blue band
Headshot rate59.2%38.2%39.9%above
Shot accuracy5.0%3.6%7.0%2.0% short
Kill/death ratio1.130.830.92above
Match win rate48.9%40.2%42.3%above

This profile matches the typical Light Blue band player on 3 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Light Blue band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGJKSPORTSROCKETPREMIER4,660 · Grey bandcsdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim59
Positioning61
Utility34

0–100 skill scores via Leetify.

Recent form

COLD47–43–10Last 10047%Win rateLWLWLLWLLL

Last 10 vs previous 10: −30pp win rate · +0.03 avg rating · −3.4pp headshot accuracy · +22ms reaction

Win rate down 30pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (+0.03), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 2–3 · 40% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 20%
  • Avg reaction 600ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 21%
  • Avg reaction 591ms

Last 20

  • 9–11 · 45% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 23%
  • 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: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+4 against its own average).

Aim5.9
Utility3.4
Positioning6.1
Opening Duels4.4
Clutch10.0

Reliable in 1v1s

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

s1mple

Plays most like s1mple 83% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower aim 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

T openings. 65% T opening-duel success — entries that actually open the round.

Areas to improve

CT openings. Opening success drops from 65% on T to 44% on CT — first contacts on the defending side are being lost.

Reaction time. 573ms 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

Aim5.9
Positioning6.1
Utility3.4
Mechanics5.7
Opening Duels6.1
Win Impact1.7

Composite 4.6/10 (Developing), 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 rating0.01−0.03
first ⅓ avg 0.03 → last ⅓ avg 0.01
Reaction time571ms+33ms
first ⅓ avg 537ms → last ⅓ avg 571ms
Headshot accuracy24.9%+2.5%
first ⅓ avg 22.4% → last ⅓ avg 24.9%

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

0.25Best match rating · 9–3 · inferno, 7 Aug →
43%Best headshot accuracy · 10–13 · boulder, 13 Aug →
375msFastest reaction time · 8–8 · inferno, 12 Aug →
13–0Biggest win · inferno, 2 Nov →

Across the last 100 tracked matches.

Highlights

7Longest win streak
8–6In matches decided by ≤2 rounds
4Overtime games

Map breakdown

ancientBest map · 80% over 5nukeWeakest map · 25% over 8
MapGradePlayedRecordWin rateAvg rating
infernoC4017–2343%0.03
mirageS107–370%0.01
nukeD82–625%0.01
dust2B84–450%0.04
anubisD62–433%-0.03
ancientS54–180%0.08
cache—42–250%0.03
boulder—42–250%0.00
office—43–175%0.04
fachwerk—33–0100%0.03
train—20–20%-0.01
vertigo—20–20%-0.02
shelter—20–20%-0.05
overpass—11–0100%0.00
italy—10–10%0.06

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (25% over 8). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Lifetime stats

33,160Lifetime kills
1.13K/D · Top 10% of Grey band
3,408Matches
48.9%Match win rate · Top 5% of Grey band
59.2%Headshot % · Top 5% of Grey band
5.0%Shot accuracy · Top 50% of Grey band
9,715MVPs
708Hours (in match)
1,516Bombs planted
272Bombs defused

Most-used weapons

Lifetime map wins

15,309office
3,174dust2
2,139inferno
720italy
702cbble
649nuke
354vertigo
172train

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

Faceit stats

Combat

4Matches
25%Win rate
0.79Avg K/D
77.8ADR
59%Headshot %

Clutches & streaks

100%1v1 clutch win
0%1v2 clutch win
1Longest win streak

Recent Faceit resultsLLWLL

MapMatchesWin rateAvg K/DAvg kills
Inferno250%1.1420.5
Dust210%0.539.0
Mirage10%0.356.0

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.

25.2%Headshot accuracy
29.3%Accuracy (enemy spotted)
30.6%Spray accuracy
75.5%Counter-strafing
11.5°Preaim
573msReaction time
65.1%T opening success
43.7%CT opening success
0.34Enemies flashed / flash
0.9%Flash assists
5.35HE damage / grenade
5.73Flashes / 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. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.3398 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Nuke

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

25% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache14–160.0313%2 Nov →
inferno13–00.0923%2 Nov →
inferno0–13-0.0521%2 Nov →
nuke13–10.0722%2 Nov →
dust28–130.0223%2 Nov →
ancient10–130.1221%2 Nov →
dust213–70.0213%2 Nov →
nuke7–13-0.0130%2 Nov →
inferno8–130.0227%2 Nov →
anubis9–13-0.0219%2 Nov →
ancient13–80.0724%2 Nov →
anubis11–13-0.0322%28 Oct →
nuke10–130.1231%28 Oct →
boulder13–6-0.0522%28 Sept →
overpass13–50.0018%28 Sept →
cache13–6-0.0231%28 Sept →
mirage6–13-0.088%21 Sept →
cache13–30.0720%21 Sept →
inferno9–5-0.0929%12 Sept →
nuke8–13-0.0441%12 Sept →
office13–60.0728%4 Sept →
train10–130.0332%25 Aug →
vertigo11–13-0.0127%23 Aug →
mirage13–5-0.0422%20 Aug →
cache4–130.0333%18 Aug →
nuke1–7-0.0614%18 Aug →
inferno6–90.0531%16 Aug →
nuke8–130.0233%14 Aug →
ancient13–10-0.0427%14 Aug →
boulder10–130.0943%13 Aug →
fachwerk13–90.0331%13 Aug →
inferno1–9-0.2321%12 Aug →
inferno9–50.0121%12 Aug →
inferno8–80.0136%12 Aug →
inferno8–8-0.0441%12 Aug →
inferno9–70.1025%12 Aug →
inferno9–7-0.0523%12 Aug →
inferno8–8-0.0124%12 Aug →
inferno4–90.0132%12 Aug →
inferno9–40.2221%12 Aug →
inferno8–80.0120%12 Aug →
inferno3–9-0.0733%12 Aug →
vertigo8–13-0.0330%11 Aug →
nuke8–13-0.0227%11 Aug →
boulder13–20.0728%11 Aug →
train12–12-0.0426%11 Aug →
office13–110.0320%11 Aug →
italy6–130.0626%11 Aug →
shelter4–13-0.0526%11 Aug →
fachwerk13–9-0.0320%11 Aug →
mirage10–13-0.0331%11 Aug →
dust210–10.1128%11 Aug →
inferno8–130.0214%10 Aug →
inferno13–110.0532%10 Aug →
anubis13–7-0.0020%10 Aug →
anubis13–60.0129%10 Aug →
mirage13–30.0735%10 Aug →
mirage13–40.0223%10 Aug →
nuke13–80.0429%10 Aug →
mirage13–80.0118%10 Aug →
dust27–130.0225%10 Aug →
inferno7–13-0.0133%8 Aug →
dust29–13-0.0628%8 Aug →
inferno13–70.1037%8 Aug →
mirage16–140.0633%8 Aug →
ancient13–30.1422%8 Aug →
ancient13–50.0831%8 Aug →
inferno7–9-0.0016%7 Aug →
inferno9–50.1331%7 Aug →
inferno9–7-0.0315%7 Aug →
inferno9–30.2039%7 Aug →
inferno9–30.2513%7 Aug →
inferno8–8-0.0611%7 Aug →
inferno8–80.1421%7 Aug →
inferno5–9-0.159%7 Aug →
inferno3–9-0.0836%7 Aug →
inferno9–20.1429%7 Aug →
inferno0–9-0.1336%7 Aug →
inferno9–130.0625%6 Aug →
mirage13–60.0715%6 Aug →
office13–80.0617%6 Aug →
mirage3–13-0.0518%6 Aug →
anubis3–13-0.1311%6 Aug →
inferno13–10-0.0613%6 Aug →
dust213–80.1318%5 Aug →
dust29–130.0224%5 Aug →
office7–130.0235%5 Aug →
inferno6–90.1626%5 Aug →
inferno8–8-0.1022%5 Aug →
inferno8–80.0523%5 Aug →
inferno9–50.1720%5 Aug →
inferno8–8-0.0910%5 Aug →
inferno9–20.2231%5 Aug →
dust213–90.0817%4 Aug →
mirage13–90.0827%4 Aug →
fachwerk13–110.0920%4 Aug →
shelter11–13-0.0532%4 Aug →
boulder6–13-0.0926%4 Aug →
anubis14–160.0028%4 Aug →
inferno16–140.0227%4 Aug →

Match data via Leetify.

Recent teammates

Milestones

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

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