Jade

Jade — CS2 Stats

76561198180558686[U:1:220292958]Steam profile ↗✓ No bans

2,803Tracked matches57%Win rate2020Tracked since
CSDB Rating3.1 LearningPositional Player
Premier CS Rating14,400Blue band · top ~31.6% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 11 Oct 2026 (4 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: 14,400 -268 30 Aug – 11 Oct · 6 days played
14,23114,668peak 14,66830 Aug11 Oct
14,677Peak Premier in tracked matches
34Days played since 2026-08-16

Premier CS Rating

  • 268 below peak (14,668)
  • -162 over 30 days · steady
  • Next: Purple band at 15,000 — 600 to go
  • Reached: Blue band · Light Blue band
  • Blue band first seen 2026-09-01
  • Light Blue band first seen 2026-09-01

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

Share this profile

CSDB.GGJadePREMIER14,400 · Blue bandcsdb.gg/stats

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Performance scores

Aim36
Positioning48
Utility3

0–100 skill scores via Leetify.

Recent form

STEADY45–42–13Last 10045%Win rateLLWLWWTLWW

Last 10 vs previous 10: −10pp win rate · −0.04 avg rating · −2.0pp headshot accuracy · +22ms 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

  • 2–3 · 40% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 11%
  • Avg reaction 544ms

Last 10

  • 5–4–1 · 50% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 12%
  • Avg reaction 528ms

Last 20

  • 11–8–1 · 55% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 13%
  • Avg reaction 516ms

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: Positional Player — Positioning stands above the rest of this profile (+2.3 against its own average).

Aim3.6
Utility0.3
Positioning4.8
Opening Duels2.3

Limited utility dependence

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

donk

Plays most like donk 69% playstyle similarity

Most alike: positioning profile, 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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Counter-strafing. Only 52% 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

Aim3.6
Positioning4.8
Utility0.3
Mechanics0.4
Opening Duels3.5
Win Impact7.4

Composite 3.1/10 (Learning), 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 rating-0.03−0.01
first ⅓ avg -0.02 → last ⅓ avg -0.03
Reaction time519ms−36ms
first ⅓ avg 555ms → last ⅓ avg 519ms
Headshot accuracy12.2%−1.7%
first ⅓ avg 13.8% → last ⅓ avg 12.2%

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

0.07Best match rating · 7–13 · train, 10 Oct →
33%Best headshot accuracy · 2–1 · train, 19 Aug →
359msFastest reaction time · 7–13 · train, 10 Oct →
13–0Biggest win · office, 5 Oct →

Across the last 100 tracked matches.

Highlights

6Longest win streak
L2Current streak
6–4In matches decided by ≤2 rounds
3Overtime games

Map breakdown

trainBest map · 60% over 10mirageWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
cacheC145–936%-0.04
ancientB147–750%-0.01
nukeC146–843%-0.03
vertigoB136–746%-0.02
trainA106–460%-0.02
infernoA95–456%-0.03
officeC73–443%-0.02
anubisC73–443%-0.03
mirageD51–420%-0.05
dust2—20–20%-0.02
overpass—20–20%0.00
shelter—11–0100%-0.03
italy—11–0100%-0.06
boulder—11–0100%0.05

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (20% over 5). Start with the 5 essential Mirage 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.

12.8%Headshot accuracy
34.6%Accuracy (enemy spotted)
45.4%Spray accuracy
51.8%Counter-strafing
15.6°Preaim
514msReaction time
50.7%T opening success
37.7%CT opening success
0.02Enemies flashed / flash
0.0%Flash assists
2.35HE damage / grenade
0.12Flashes / 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

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 15.605° — above the 12° mark we flag

    Aim Training →
  2. 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 12.8339% — below the 15% mark we flag

    Aim Training →
  3. 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 0.0202 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Mirage

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
office11–13-0.0615%14 Oct →
cache10–13-0.0716%14 Oct →
anubis13–3-0.015%12 Oct →
cache10–13-0.0512%11 Oct →
ancient13–11-0.029%11 Oct →
vertigo13–50.036%11 Oct →
office12–12-0.0521%11 Oct →
nuke7–13-0.106%11 Oct →
cache13–5-0.0324%10 Oct →
train13–2-0.017%10 Oct →
inferno9–13-0.0512%10 Oct →
train7–130.0721%10 Oct →
shelter13–9-0.0313%7 Oct →
mirage13–7-0.0412%7 Oct →
anubis13–6-0.048%7 Oct →
vertigo5–13-0.0116%6 Oct →
cache13–70.0312%5 Oct →
office13–00.0512%5 Oct →
nuke11–130.0218%4 Oct →
ancient13–7-0.0016%4 Oct →
ancient15–15-0.0310%4 Oct →
inferno13–3-0.0211%4 Oct →
office8–3-0.070%3 Oct →
anubis13–70.0010%3 Oct →
train4–13-0.0021%3 Oct →
inferno3–13-0.128%3 Oct →
train5–13-0.096%2 Oct →
vertigo10–13-0.0514%2 Oct →
nuke13–4-0.0219%30 Sept →
inferno13–9-0.0615%30 Sept →
mirage12–12-0.028%30 Sept →
cache13–7-0.058%29 Sept →
vertigo13–4-0.0111%28 Sept →
nuke13–60.0425%28 Sept →
anubis5–13-0.0711%27 Sept →
nuke0–13-0.106%27 Sept →
dust212–120.0116%27 Sept →
inferno13–8-0.0118%27 Sept →
office13–7-0.096%27 Sept →
nuke10–13-0.0615%27 Sept →
mirage10–13-0.0711%27 Sept →
vertigo12–120.0514%27 Sept →
cache7–13-0.0511%26 Sept →
train13–7-0.0215%26 Sept →
italy9–1-0.068%26 Sept →
boulder13–00.0515%26 Sept →
train13–8-0.0610%26 Sept →
vertigo13–50.0512%26 Sept →
nuke13–5-0.0214%26 Sept →
cache4–13-0.107%26 Sept →
inferno12–12-0.0610%26 Sept →
ancient13–11-0.0313%26 Sept →
vertigo13–70.0115%25 Sept →
ancient11–13-0.0315%24 Sept →
vertigo12–12-0.079%24 Sept →
nuke12–12-0.0410%23 Sept →
cache7–13-0.0516%20 Sept →
vertigo13–2-0.016%20 Sept →
office12–120.0015%19 Sept →
overpass10–13-0.0516%19 Sept →
cache2–13-0.063%18 Sept →
anubis9–13-0.0615%17 Sept →
cache6–13-0.0420%17 Sept →
cache13–11-0.0325%16 Sept →
ancient10–13-0.0111%16 Sept →
anubis12–12-0.0119%16 Sept →
nuke13–90.0019%16 Sept →
cache3–13-0.0718%15 Sept →
nuke13–6-0.0215%15 Sept →
inferno11–130.0328%15 Sept →
train0–13-0.089%15 Sept →
ancient2–13-0.0119%15 Sept →
mirage0–13-0.043%15 Sept →
ancient3–130.0110%7 Sept →
anubis5–130.0113%5 Sept →
office4–130.0511%5 Sept →
dust212–16-0.0624%5 Sept →
overpass12–120.0618%4 Sept →
ancient13–80.049%4 Sept →
vertigo12–12-0.0112%4 Sept →
ancient3–13-0.0314%2 Sept →
vertigo2–13-0.0721%1 Sept →
nuke2–13-0.0428%1 Sept →
cache7–13-0.0614%1 Sept →
ancient1–13-0.0713%1 Sept →
ancient16–140.0116%30 Aug →
ancient13–60.0616%19 Aug →
cache13–100.0415%19 Aug →
train2–10.0333%19 Aug →
inferno13–5-0.077%18 Aug →
ancient13–10-0.048%18 Aug →
nuke8–13-0.046%18 Aug →
train13–4-0.0317%18 Aug →
vertigo6–13-0.088%18 Aug →
mirage8–13-0.097%18 Aug →
nuke12–12-0.043%17 Aug →
vertigo13–4-0.0512%16 Aug →
nuke13–30.0210%16 Aug →
train13–50.049%16 Aug →
inferno13–110.0612%16 Aug →

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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