ジャラド

ジャラド — CS2 Stats

JP76561198920747179[U:1:960481451]Steam profile ↗✓ No bans

248Tracked matches68%Win rate2021Tracked since
CSDB Rating7.1 StrongAll-Rounder
Premier CS Rating20,437Top 50% of 204,793 CSDB-tracked playersPink band · top ~8% of ranked players (population est.)
CSDB Leaderboard#74915 of 252069 tracked
FaceitLevel 3Top 90.6% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 26 Sep 2026 (19 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 248 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 20,437 +6,653 29 May – 26 Sept · 27 days played
13,78420,437peak 20,43729 May26 Sept
20,560Peak Premier in tracked matches
47Days played since 2025-05-29

Premier CS Rating

  • At peak — 20,437
  • 0 over 30 days · steady
  • Next: Red band at 25,000 — 4,563 to go
  • Reached: Pink band · Purple band · Blue band · Light Blue band
  • Pink band first seen 2026-09-26
  • Purple band first seen 2026-09-26

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

Share this profile

CSDB.GGジャラドFACEITLevel 3STANDINGTop 90.6% of rankedPREMIER20,437 · Pink bandcsdb.gg/stats

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Performance scores

Aim75
Positioning64
Utility66

0–100 skill scores via Leetify.

Recent form

STEADY57–41–2Last 10057%Win rateLWWWWLWTWL

Last 10 vs previous 10: +10pp win rate · +0.01 avg rating · +1.5pp headshot accuracy · −30ms 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

  • 4–1 · 80% win rate
  • Avg rating 0.06
  • Avg headshot accuracy 21%
  • Avg reaction 496ms

Last 10

  • 6–3–1 · 60% win rate
  • Avg rating 0.04
  • Avg headshot accuracy 21%
  • Avg reaction 459ms

Last 20

  • 11–7–2 · 55% win rate
  • Avg rating 0.04
  • Avg headshot accuracy 20%
  • Avg reaction 474ms

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-Rounder — No style dimension stands clear of the others in this profile.

Aim7.5
Utility6.6
Positioning6.4
Opening Duels7.1

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 79% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: 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

Strengths

T openings. 60% T opening-duel success — entries that actually open the round.

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

Aim7.5
Positioning6.4
Utility6.6
Mechanics5.3
Opening Duels6.8
Win Impact10.0

Composite 7.1/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.05+0.03
first ⅓ avg 0.01 → last ⅓ avg 0.05
Reaction time523ms−136ms
first ⅓ avg 658ms → last ⅓ avg 523ms
Headshot accuracy23.2%+1.3%
first ⅓ avg 21.9% → last ⅓ avg 23.2%

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

0.20Best match rating · 13–6 · ancient, 24 Mar →
55%Best headshot accuracy · 13–8 · dust2, 14 Jul →
375msFastest reaction time · 13–6 · anubis, 17 Aug →
13–1Biggest win · mirage, 21 Nov →

Across the last 100 tracked matches.

Highlights

10Longest win streak
9–10In matches decided by ≤2 rounds
12Overtime games

Map breakdown

anubisBest map · 83% over 6dust2Weakest map · 43% over 7
MapGradePlayedRecordWin rateAvg rating
ancientA2715–1256%0.04
mirageA1911–858%0.03
infernoB179–853%0.04
nukeA127–558%0.02
dust2C73–443%0.01
anubisS65–183%0.03
trainS64–267%-0.02
cache—32–167%-0.01
overpass—31–233%-0.03

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (43% over 7). 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.

21.9%Headshot accuracy
32.3%Accuracy (enemy spotted)
35.5%Spray accuracy
74.0%Counter-strafing
8.2°Preaim
526msReaction time
60.3%T opening success
54.4%CT opening success
0.58Enemies flashed / flash
6.9%Flash assists
11.93HE damage / grenade
15.74Flashes / match

Recommended for you

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.

43% win rate across 7 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
nuke9–130.0013%23 Aug →
cache13–100.0423%23 Aug →
ancient13–60.0325%23 Aug →
ancient13–20.1122%23 Aug →
anubis13–80.1122%23 Aug →
inferno6–130.0520%17 Aug →
anubis13–60.0638%17 Aug →
mirage15–15-0.0012%17 Aug →
inferno13–30.1220%17 Aug →
ancient6–13-0.0713%17 Aug →
inferno15–150.0223%17 Aug →
mirage6–130.0817%16 Aug →
anubis16–120.0110%16 Aug →
ancient13–110.0812%16 Aug →
ancient13–70.0531%13 Aug →
cache13–7-0.0126%12 Aug →
ancient10–13-0.0011%11 Aug →
dust210–13-0.0314%22 Jul →
cache8–13-0.0426%22 Jul →
inferno13–110.1224%14 Apr →
dust216–140.0428%30 Mar →
ancient13–80.0027%26 Mar →
nuke13–20.1248%26 Mar →
dust29–13-0.0129%24 Mar →
mirage16–120.0718%24 Mar →
ancient13–60.2032%24 Mar →
inferno13–90.0822%24 Mar →
nuke10–130.0025%23 Mar →
ancient13–50.0417%23 Mar →
anubis13–60.0428%22 Mar →
inferno7–130.1134%22 Mar →
ancient13–80.1227%22 Mar →
ancient0–13-0.0329%17 Mar →
mirage14–16-0.0227%16 Mar →
nuke13–7-0.0225%15 Mar →
inferno11–13-0.0126%15 Feb →
mirage13–80.0329%15 Feb →
train13–6-0.0245%21 Nov →
mirage13–10.0436%21 Nov →
ancient13–60.0633%20 Nov →
nuke13–110.0337%23 Oct →
nuke16–130.0919%1 Oct →
inferno13–30.1418%1 Oct →
nuke13–110.0221%30 Sept →
ancient13–30.0933%30 Sept →
mirage13–110.0845%30 Sept →
inferno1–13-0.0137%30 Sept →
mirage10–130.0021%28 Sept →
train10–13-0.0722%28 Sept →
mirage14–16-0.0225%17 Sept →
ancient14–16-0.0132%3 Sept →
ancient11–130.0315%31 Aug →
train13–90.0024%29 Aug →
mirage11–13-0.0215%28 Aug →
inferno13–50.0123%28 Aug →
inferno13–60.0522%27 Aug →
nuke8–13-0.0115%27 Aug →
ancient13–16-0.0214%26 Aug →
inferno13–50.0813%26 Aug →
inferno13–9-0.0720%26 Aug →
nuke14–16-0.0211%25 Aug →
ancient13–50.0418%25 Aug →
overpass13–9-0.0318%24 Aug →
dust210–13-0.0118%24 Aug →
nuke13–20.0825%24 Aug →
mirage13–70.0818%24 Aug →
mirage13–60.0918%24 Aug →
inferno5–13-0.0424%21 Aug →
mirage13–50.0328%21 Aug →
ancient6–13-0.0135%19 Aug →
inferno10–130.0825%19 Aug →
mirage13–50.1317%19 Aug →
ancient10–130.0918%18 Aug →
ancient7–10.1410%18 Aug →
dust24–130.0122%18 Aug →
mirage13–110.1025%18 Aug →
mirage9–130.0337%18 Aug →
overpass4–13-0.0216%17 Aug →
ancient13–70.0116%17 Aug →
nuke10–130.0121%17 Aug →
inferno13–7-0.0211%17 Aug →
mirage13–40.0418%17 Aug →
ancient11–130.0038%15 Aug →
ancient11–13-0.0414%6 Aug →
train13–8-0.0228%6 Aug →
overpass1–9-0.048%6 Aug →
ancient6–130.0226%4 Aug →
dust213–11-0.0020%21 Jul →
dust213–80.0655%14 Jul →
train13–7-0.0233%14 Jul →
anubis13–7-0.057%21 Jun →
nuke13–9-0.0110%16 Jun →
train12–160.0336%16 Jun →
anubis11–13-0.0121%13 Jun →
ancient13–70.0521%13 Jun →
ancient7–130.0120%5 Jun →
mirage13–11-0.0114%2 Jun →
ancient13–90.0115%2 Jun →
mirage4–13-0.1122%29 May →
inferno6–13-0.0710%29 May →

Match data via Leetify.

Recent teammates

Milestones

100 Matches10-Win Streak
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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