Token

Token — CS2 Stats

76561198190538071[U:1:230272343]Steam profile ↗✓ No bans

446Tracked matches45%Win rate2023Tracked since
CSDB Rating3.9 LearningSupport
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 10,537 +2,717 17 May – 5 Jan · 36 days played
7,82011,358peak 11,35817 May5 Jan
11,358Peak Premier in tracked matches
58Days played since 2025-05-17

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

Performance scores

Aim42
Positioning28
Utility38

0–100 skill scores via Leetify.

Recent form

COLD52–47–1Last 10052%Win rateWLWLLLLLLT

Last 10 vs previous 10: −40pp win rate · −0.03 avg rating · −0.3pp headshot accuracy · −9ms 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 -0.05
  • Avg headshot accuracy 8%
  • Avg reaction 708ms

Last 10

  • 2–7–1 · 20% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 9%
  • Avg reaction 642ms

Last 20

  • 8–11–1 · 40% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 9%
  • Avg reaction 646ms

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 (+1.5 against its own average).

Aim4.2
Utility3.8
Positioning2.8
Opening Duels0.2

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

ZywOo

Plays most like ZywOo 85% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-duel success; 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

T-side openings. Opening success drops from 36% on CT to 21% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 666ms 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

Aim4.2
Positioning2.8
Utility3.8
Mechanics7.0
Opening Duels0.8
Win Impact3.3

Composite 3.9/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.03−0.02
first ⅓ avg -0.02 → last ⅓ avg -0.03
Reaction time650ms+27ms
first ⅓ avg 624ms → last ⅓ avg 650ms
Headshot accuracy9.4%−0.3%
first ⅓ avg 9.7% → last ⅓ avg 9.4%

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

0.08Best match rating · 13–3 · nuke, 13 Jun →
23%Best headshot accuracy · 4–13 · inferno, 2 May →
352msFastest reaction time · 2–8 · inferno, 14 May →
13–1Biggest win · mirage, 26 Apr →

Across the last 100 tracked matches.

Highlights

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

Map breakdown

infernoBest map · 62% over 29dust2Weakest map · 38% over 13
MapGradePlayedRecordWin rateAvg rating
infernoA2918–1162%-0.02
nukeA148–657%-0.01
dust2C135–838%-0.03
mirageB137–654%-0.02
ancientA116–555%-0.03
anubisC104–640%-0.05
cache—41–325%-0.04
train—41–325%-0.04
overpass—22–0100%-0.05

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (38% over 13). 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.

9.1%Headshot accuracy
31.1%Accuracy (enemy spotted)
34.4%Spray accuracy
81.5%Counter-strafing
10.6°Preaim
666msReaction time
20.6%T opening success
36.2%CT opening success
0.45Enemies flashed / flash
6.4%Flash assists
5.29HE damage / grenade
4.00Flashes / 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. 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 9.0872% — below the 15% mark we flag

    Aim Training →
  2. 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 0.4507 — below the 0.5 mark we flag

    Grenade Lineups →
  3. 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 20.5707% — below the 40% mark we flag

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.

38% win rate across 13 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
dust213–8-0.076%31 May →
dust27–13-0.106%31 May →
cache13–9-0.054%22 May →
mirage7–13-0.0214%22 May →
ancient9–13-0.029%22 May →
inferno8–13-0.0415%22 May →
inferno2–8-0.065%14 May →
cache8–13-0.096%6 May →
dust25–13-0.0612%6 May →
cache12–120.009%6 May →
inferno4–13-0.0423%2 May →
cache11–13-0.046%2 May →
mirage13–1-0.0417%26 Apr →
ancient13–4-0.043%10 Apr →
mirage1–10-0.044%6 Feb →
inferno13–5-0.016%6 Feb →
inferno13–60.038%5 Feb →
nuke13–30.047%28 Jan →
anubis13–80.003%22 Jan →
nuke6–13-0.0813%22 Jan →
nuke13–60.023%5 Jan →
ancient5–13-0.0110%5 Jan →
inferno13–70.0218%8 Dec →
inferno13–11-0.0110%7 Dec →
train13–8-0.057%7 Dec →
dust210–13-0.034%18 Nov →
mirage9–13-0.0813%17 Nov →
ancient13–8-0.020%17 Nov →
inferno10–13-0.0817%16 Nov →
dust25–13-0.0514%16 Nov →
mirage13–110.0115%15 Nov →
dust23–13-0.107%9 Nov →
inferno13–80.0014%9 Nov →
inferno14–120.0416%5 Nov →
train10–13-0.0812%5 Nov →
ancient16–14-0.0915%2 Nov →
dust216–13-0.0414%28 Oct →
ancient13–50.0613%25 Oct →
inferno5–13-0.0413%25 Oct →
overpass13–9-0.019%23 Oct →
inferno7–13-0.014%23 Oct →
nuke8–13-0.059%20 Oct →
mirage13–9-0.008%16 Oct →
overpass13–8-0.087%16 Oct →
mirage12–16-0.1017%19 Sept →
train10–13-0.0614%19 Sept →
ancient14–16-0.048%7 Sept →
inferno13–7-0.079%7 Sept →
mirage13–10.045%7 Sept →
inferno13–9-0.0210%1 Sept →
nuke11–130.007%11 Aug →
ancient2–5-0.125%27 Jul →
inferno13–6-0.047%27 Jul →
inferno13–60.006%27 Jul →
mirage1–13-0.022%26 Jul →
inferno12–16-0.0410%25 Jul →
ancient13–8-0.0112%25 Jul →
mirage9–13-0.0113%20 Jul →
inferno9–40.0312%20 Jul →
nuke6–13-0.1114%20 Jul →
mirage13–4-0.055%28 Jun →
anubis9–13-0.036%28 Jun →
nuke6–13-0.054%25 Jun →
inferno13–8-0.0122%25 Jun →
ancient13–40.066%23 Jun →
inferno13–2-0.0911%23 Jun →
anubis7–13-0.0216%21 Jun →
dust25–13-0.0413%20 Jun →
nuke16–140.009%16 Jun →
nuke13–80.014%15 Jun →
anubis13–6-0.068%15 Jun →
train11–130.016%15 Jun →
nuke13–30.089%13 Jun →
inferno13–20.0310%13 Jun →
anubis13–11-0.107%12 Jun →
inferno9–13-0.0323%10 Jun →
anubis13–6-0.068%9 Jun →
inferno2–130.0118%9 Jun →
nuke13–3-0.0318%8 Jun →
anubis6–13-0.066%4 Jun →
dust213–9-0.019%4 Jun →
nuke10–13-0.026%3 Jun →
inferno13–20.069%2 Jun →
anubis8–13-0.0712%2 Jun →
nuke13–60.034%31 May →
inferno5–13-0.1314%31 May →
ancient7–13-0.0513%29 May →
dust24–13-0.0213%28 May →
nuke13–11-0.0213%28 May →
inferno13–9-0.0214%28 May →
anubis12–16-0.063%22 May →
inferno13–11-0.017%21 May →
mirage13–40.004%20 May →
inferno11–13-0.0712%19 May →
mirage13–80.039%18 May →
dust211–130.037%18 May →
dust213–40.0515%18 May →
inferno13–7-0.005%17 May →
dust213–60.0010%17 May →
anubis10–13-0.045%17 May →

Match data via Leetify.

Recent teammates

Milestones

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

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