jwhite

jwhite — CS2 Stats

US76561197960518649[U:1:252921]Steam profile ↗✓ No bans

1,902Tracked matches60%Win rate2020Tracked since
CSDB Rating6.4 SolidSupport
FaceitLevel 8 · 1,992 ELOTop 31.2% of ranked FACEIT players
WingmanMaster Guardian Elite
Ladder ranks via Leetify

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CSDB.GGjwhiteFACEITLevel 8 · 1,992 ELOSTANDINGTop 31.2% of rankedcsdb.gg/stats

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Performance scores

Aim75
Positioning58
Utility69

0–100 skill scores via Leetify.

Recent form

HOT45–47–8Last 10045%Win rateWWWWWWLWWW

Last 10 vs previous 10: +60pp win rate · −0.02 avg rating · −3.6pp headshot accuracy · +18ms reaction

Win rate up 60pp 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 (−0.02), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 5–0 · 100% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 16%
  • Avg reaction 589ms

Last 10

  • 9–1 · 90% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 15%
  • Avg reaction 577ms

Last 20

  • 12–8 · 60% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 16%
  • Avg reaction 569ms

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 (+2.1 against its own average).

Aim7.5
Utility6.9
Positioning5.8
Opening Duels3.5
Clutch3.2

Strong 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

ZywOo

Plays most like ZywOo 88% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower positioning profile; 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. 559ms 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

Aim7.5
Positioning5.8
Utility6.9
Mechanics7.1
Opening Duels4.2
Win Impact8.3

Composite 6.4/10 (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 rating0.01−0.04
first ⅓ avg 0.05 → last ⅓ avg 0.01
Reaction time567ms−63ms
first ⅓ avg 630ms → last ⅓ avg 567ms
Headshot accuracy17.2%+2.9%
first ⅓ avg 14.3% → last ⅓ avg 17.2%

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

0.25Best match rating · 13–5 · mirage, 21 Jun →
31%Best headshot accuracy · 11–5 · ancient, 30 Aug →
422msFastest reaction time · 13–2 · anubis, 12 Oct →
13–1Biggest win · inferno, 22 Aug →

Across the last 100 tracked matches.

Highlights

6Longest win streak
W6Current streak
10–5In matches decided by ≤2 rounds
5Overtime games

Map breakdown

ancientBest map · 100% over 5trainWeakest map · 0% over 7
MapGradePlayedRecordWin rateAvg rating
infernoC207–1335%0.06
nukeA1710–759%0.04
cacheC146–843%0.03
dust2B115–645%-0.02
vertigoC94–544%0.05
mirageC73–443%0.07
trainD70–70%0.05
anubisB63–350%-0.00
ancientS55–0100%0.01
debris—10–10%0.03
italy—11–0100%0.08
office—11–0100%0.08
overpass—10–10%-0.01

Across the last 100 tracked matches.

Faceit stats

Combat

1,126Matches
49%Win rate
1.03Avg K/D
75.8ADR
41%Headshot %

Clutches & streaks

36%1v1 clutch win
19%1v2 clutch win
11Longest win streak

Recent Faceit resultsWWWWL

MapMatchesWin rateAvg K/DAvg kills
Ancient16741%0.9715.3
Inferno16059%1.0916.4
Nuke11363%1.0314.3
Anubis8341%0.8715.2
Dust25746%0.9314.8
Mirage3944%0.8814.1
Vertigo1030%1.0215.2
Cache580%1.1219.8

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.

16.9%Headshot accuracy
40.9%Accuracy (enemy spotted)
37.4%Spray accuracy
82.1%Counter-strafing
12.1°Preaim
559msReaction time
39.7%T opening success
53.8%CT opening success
0.60Enemies flashed / flash
8.5%Flash assists
8.03HE damage / grenade
12.34Flashes / 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 12.1063° — above the 12° mark we flag

    Aim Training →
Spend your practice time on Train

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

0% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
inferno13–90.0317%17 Oct →
nuke13–80.0110%17 Oct →
nuke13–5-0.0120%17 Oct →
inferno13–60.0217%17 Oct →
anubis13–2-0.0514%12 Oct →
inferno13–110.0219%12 Oct →
nuke0–13-0.074%4 Oct →
nuke13–8-0.0720%27 Sept →
dust213–11-0.0711%23 Sept →
ancient13–100.0314%23 Sept →
dust28–13-0.0621%23 Sept →
inferno13–60.0317%23 Sept →
nuke8–13-0.0316%20 Sept →
inferno7–130.0919%20 Sept →
dust26–13-0.044%4 Sept →
inferno9–13-0.0216%4 Sept →
inferno10–130.1314%30 Aug →
mirage11–40.0518%30 Aug →
dust24–13-0.0626%30 Aug →
ancient11–5-0.0331%30 Aug →
anubis13–8-0.0023%30 Aug →
cache16–140.0713%30 Aug →
dust24–13-0.0517%28 Aug →
inferno8–130.0622%28 Aug →
cache6–130.0423%28 Aug →
vertigo13–11-0.0217%28 Aug →
dust213–100.0119%24 Aug →
nuke13–110.0219%22 Aug →
train7–130.0115%22 Aug →
vertigo13–40.1615%22 Aug →
inferno13–10.1225%22 Aug →
inferno14–16-0.0215%15 Aug →
cache13–60.0319%14 Aug →
nuke13–110.1719%8 Aug →
inferno8–130.0415%8 Aug →
nuke13–40.115%8 Aug →
mirage5–13-0.049%8 Aug →
ancient13–90.0221%8 Aug →
cache5–130.0913%1 Aug →
inferno5–130.0519%1 Aug →
vertigo0–13-0.0712%1 Aug →
inferno12–120.1214%1 Aug →
inferno1–90.0114%1 Aug →
vertigo12–120.0217%1 Aug →
dust213–70.0616%1 Aug →
ancient13–80.0313%1 Aug →
anubis13–90.0518%1 Aug →
nuke12–12-0.0323%1 Aug →
cache15–15-0.0412%24 Jul →
train12–120.059%24 Jul →
train11–130.056%19 Jul →
vertigo13–110.0816%19 Jul →
inferno12–120.0218%19 Jul →
nuke13–70.1523%19 Jul →
cache7–130.0319%19 Jul →
mirage8–130.1014%11 Jul →
anubis9–13-0.057%11 Jul →
cache19–17-0.039%11 Jul →
nuke13–4-0.0216%11 Jul →
debris8–80.0321%11 Jul →
cache9–130.1315%28 Jun →
mirage9–130.0610%28 Jun →
nuke9–130.1017%28 Jun →
italy13–110.0811%28 Jun →
office13–100.0811%28 Jun →
cache4–10.1024%28 Jun →
dust213–11-0.0519%28 Jun →
nuke13–70.0614%21 Jun →
inferno13–90.1819%21 Jun →
train10–130.1118%21 Jun →
mirage10–130.0814%21 Jun →
train8–130.0313%21 Jun →
train9–130.0721%21 Jun →
mirage13–50.2518%21 Jun →
inferno2–130.0417%21 Jun →
dust213–90.067%6 Jun →
mirage13–100.0311%6 Jun →
vertigo12–120.1211%6 Jun →
train4–130.0423%6 Jun →
inferno6–130.0312%6 Jun →
ancient13–90.0119%6 Jun →
vertigo6–130.0617%4 Jun →
vertigo13–100.0414%4 Jun →
anubis3–130.056%25 May →
cache5–130.0010%25 May →
dust26–13-0.0113%25 May →
inferno13–90.1118%24 May →
nuke13–50.1012%24 May →
vertigo8–130.0213%24 May →
inferno9–130.088%24 May →
nuke11–130.2124%24 May →
anubis11–13-0.0213%24 May →
nuke10–13-0.0615%24 May →
overpass10–13-0.017%23 May →
nuke9–13-0.0114%17 May →
dust212–16-0.0217%17 May →
cache11–130.0323%3 May →
cache2–13-0.1110%3 May →
cache13–9-0.0310%1 May →
cache13–50.0710%1 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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