Dean

Dean — CS2 Stats

76561197960303506[U:1:37778]Steam profile ↗✓ No bans

740Tracked matches43%Win rate2021Tracked since
CSDB Rating4.0 DevelopingSupport
WingmanLegendary Eagle
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 30 Aug 2026 (34 days ago). Ranks are recorded once per day this page is viewed.

+12Tracked matches · now 740
+2.0ppWin rate · 41.4% → 43.3%

Rating over time

Premier CS Rating: 12,030 -599 25 Mar – 23 Jun · 36 days played
11,31114,366peak 14,36625 Mar23 Jun
14,686Peak Premier in tracked matches
67Days played since 2025-12-20

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

Performance scores

Aim38
Positioning48
Utility56

0–100 skill scores via Leetify.

Recent form

STEADY47–50–3Last 10047%Win rateWLLWLWWWLL

Last 10 vs previous 10: 0pp win rate · +0.01 avg rating · −2.8pp headshot accuracy · +4ms reaction

Win rate 0pp 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 9%
  • Avg reaction 583ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 11%
  • Avg reaction 636ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 12%
  • Avg reaction 634ms

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 (+1.9 against its own average).

Aim3.8
Utility5.6
Positioning4.8
Opening Duels0.8

Strong T-side openerLimited 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

Twistzz

Plays most like Twistzz 63% playstyle similarity

Most alike: positioning profile, utility contribution.

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

CT openings. Opening success drops from 45% on T to 25% on CT — first contacts on the defending side are being lost.

Reaction time. 636ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 67% 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

Aim3.8
Positioning4.8
Utility5.6
Mechanics3.8
Opening Duels1.9
Win Impact2.8

Composite 4.0/10 (Developing), 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 rating0.00−0.01
first ⅓ avg 0.01 → last ⅓ avg 0.00
Reaction time643ms−18ms
first ⅓ avg 662ms → last ⅓ avg 643ms
Headshot accuracy13.0%−1.5%
first ⅓ avg 14.6% → last ⅓ avg 13.0%

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

0.19Best match rating · 9–5 · vertigo, 4 May →
40%Best headshot accuracy · 10–13 · inferno, 18 May →
445msFastest reaction time · 8–13 · ancient, 27 Sept →
13–0Biggest win · inferno, 9 Apr →

Across the last 100 tracked matches.

Highlights

7Longest win streak
7–10In matches decided by ≤2 rounds
8Overtime games

Map breakdown

nukeBest map · 56% over 9ancientWeakest map · 42% over 12
MapGradePlayedRecordWin rateAvg rating
dust2C3616–2044%-0.00
infernoB3016–1453%-0.00
ancientC125–742%0.00
nukeA95–456%-0.01
cache—31–233%0.02
poseidon—30–30%-0.07
mirage—21–150%0.05
anubis—20–20%0.03
vertigo—11–0100%0.19
overpass—11–0100%0.08
train—11–0100%0.02

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (42% over 12). Start with the 6 essential Ancient 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.

12.9%Headshot accuracy
32.1%Accuracy (enemy spotted)
36.7%Spray accuracy
67.2%Counter-strafing
11.7°Preaim
636msReaction time
44.9%T opening success
25.2%CT opening success
0.62Enemies flashed / flash
9.1%Flash assists
12.48HE damage / grenade
4.87Flashes / 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 12.9022% — below the 15% mark we flag

    Aim Training →
  2. Advanced Mechanics

    Losing the first CT duel repeatedly usually means holding angles that favour the peeker.

    CT opening duels 25.182% — below the 40% mark we flag

Spend your practice time on Ancient

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

42% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust213–70.0110%2 Oct →
inferno11–130.0211%1 Oct →
mirage11–130.107%28 Sept →
dust213–50.0611%27 Sept →
ancient8–130.015%27 Sept →
mirage13–10-0.009%24 Sept →
dust213–6-0.0521%23 Sept →
inferno13–50.0210%23 Sept →
dust29–13-0.1112%9 Sept →
dust211–130.0613%7 Sept →
dust213–110.0213%3 Sept →
inferno12–160.0411%1 Sept →
dust25–130.038%30 Jul →
nuke11–130.028%21 Jul →
inferno13–11-0.0918%20 Jul →
cache8–13-0.0211%16 Jul →
cache13–60.0819%13 Jul →
inferno13–10-0.0114%23 Jun →
inferno1–9-0.1120%18 Jun →
dust213–110.0312%15 Jun →
dust28–13-0.0628%8 Jun →
inferno13–20.1214%8 Jun →
nuke9–130.0210%5 Jun →
dust210–13-0.0113%4 Jun →
dust28–13-0.0414%3 Jun →
poseidon3–9-0.0711%3 Jun →
dust213–70.0116%2 Jun →
dust24–13-0.0215%2 Jun →
dust28–13-0.0517%1 Jun →
nuke13–20.018%1 Jun →
anubis14–160.0915%31 May →
nuke5–13-0.0416%29 May →
dust27–13-0.0210%29 May →
inferno13–11-0.0411%25 May →
anubis11–13-0.0223%23 May →
dust212–12-0.0415%21 May →
inferno9–130.009%20 May →
inferno13–110.0417%19 May →
ancient13–90.039%19 May →
inferno13–10.060%19 May →
inferno7–5-0.000%19 May →
inferno10–13-0.0340%18 May →
ancient8–13-0.0517%5 May →
inferno11–13-0.0112%5 May →
vertigo9–50.1923%4 May →
ancient13–9-0.029%3 May →
ancient8–13-0.0711%30 Apr →
ancient13–80.0511%30 Apr →
dust212–160.0216%29 Apr →
cache11–130.0115%29 Apr →
inferno13–7-0.045%26 Apr →
inferno5–130.0120%22 Apr →
nuke13–10-0.078%22 Apr →
dust213–90.1018%21 Apr →
poseidon4–9-0.2013%21 Apr →
nuke13–8-0.028%17 Apr →
ancient9–13-0.0214%17 Apr →
inferno6–13-0.0718%16 Apr →
ancient9–130.0114%15 Apr →
dust213–9-0.0121%15 Apr →
inferno13–90.0128%12 Apr →
inferno3–13-0.0718%12 Apr →
ancient10–13-0.025%11 Apr →
dust27–13-0.0321%11 Apr →
dust26–13-0.0526%11 Apr →
nuke13–90.058%11 Apr →
inferno13–0-0.013%9 Apr →
ancient6–13-0.0314%9 Apr →
ancient13–60.039%8 Apr →
inferno15–15-0.0312%5 Apr →
inferno12–16-0.0123%5 Apr →
dust216–120.0210%1 Apr →
dust213–100.0614%31 Mar →
dust22–13-0.0019%31 Mar →
poseidon8–80.0523%31 Mar →
nuke13–100.0024%30 Mar →
dust27–13-0.0711%28 Mar →
ancient13–70.1215%28 Mar →
inferno8–130.0217%26 Mar →
inferno13–40.0315%25 Mar →
dust213–30.0715%25 Mar →
inferno13–110.0615%19 Mar →
dust213–100.0418%13 Mar →
overpass13–80.0811%13 Mar →
inferno13–30.013%11 Mar →
dust213–80.025%6 Mar →
dust211–13-0.0511%6 Mar →
inferno13–60.0913%6 Mar →
inferno3–13-0.0416%2 Mar →
dust210–130.0114%26 Feb →
dust28–10.1014%25 Feb →
dust24–13-0.0020%25 Feb →
inferno13–80.0112%24 Feb →
dust214–160.037%22 Feb →
inferno8–13-0.0720%30 Jan →
dust213–90.0219%16 Jan →
nuke5–13-0.0810%16 Jan →
dust213–9-0.0211%9 Jan →
train13–90.0217%20 Dec →
dust213–16-0.0623%20 Dec →

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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