WalkEmDownBrennie

WalkEmDownBrennie — CS2 Stats

CA76561198843625511[U:1:883359783]Steam profile ↗✓ No bans

436Tracked matches45%Win rate2020Tracked since
1,701Hours in CS26Hrs last 2 wks
CSDB Rating6.3 SolidPositional Player
Premier CS Rating11,869Blue band · top ~45% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 30 Oct 2026 (yesterday). 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: 11,869 -3,493 4 Sept – 30 Oct · 28 days played
11,86915,362peak 15,3624 Sept30 Oct
15,362Peak Premier in tracked matches
33Days played since 2026-09-04

Premier CS Rating

  • 3,493 below peak (15,362)
  • -2,349 over 30 days · declining
  • Next: Purple band at 15,000 — 3,131 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-09-04
  • Blue band first seen 2026-09-04

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

How this compares with the same rank

Median values for Blue band among CSDB-tracked players (n=21,222), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerBlue band medianPurple band medianvs Purple band
Headshot rate34.9%42.0%44.4%9.4% short
Shot accuracy17.7%9.6%11.9%above
Kill/death ratio0.980.981.030.05 short
Match win rate38.9%43.8%45.2%6.3% short

This profile matches the typical Purple band player on 1 of 4 comparable metrics.

Widest gap: Headshot rate. That is the metric furthest from the Purple band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGWalkEmDownBrenniePREMIER11,869 · Blue bandcsdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim80
Positioning71
Utility57

0–100 skill scores via Leetify.

Recent form

STEADY42–56–2Last 10042%Win rateLLLLWWWLWL

Last 10 vs previous 10: −10pp win rate · +0.02 avg rating · −2.2pp 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

  • 1–4 · 20% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 11%
  • Avg reaction 489ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 12%
  • Avg reaction 524ms

Last 20

  • 9–10–1 · 45% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 14%
  • Avg reaction 509ms

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 (+1.1 against its own average).

Aim8.0
Utility5.7
Positioning7.1
Opening Duels5.3

Effective flashes

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

m0NESY

Plays most like m0NESY 91% playstyle similarity

Most alike: positioning profile, utility contribution.

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. 61% 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

Aim8.0
Positioning7.1
Utility5.7
Mechanics5.9
Opening Duels7.1
Win Impact3.3

Composite 6.3/10 (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 rating0.01−0.02
first ⅓ avg 0.03 → last ⅓ avg 0.01
Reaction time507ms−75ms
first ⅓ avg 582ms → last ⅓ avg 507ms
Headshot accuracy14.2%+0.1%
first ⅓ avg 14.0% → last ⅓ avg 14.2%

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

0.14Best match rating · 5–13 · mirage, 1 Oct →
33%Best headshot accuracy · 4–13 · dust2, 26 Oct →
391msFastest reaction time · 13–11 · dust2, 25 Oct →
13–0Biggest win · cache, 8 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L4Current streak
6–11In matches decided by ≤2 rounds
6Overtime games

Map breakdown

nukeBest map · 55% over 11ancientWeakest map · 0% over 6
MapGradePlayedRecordWin rateAvg rating
mirageB3316–1748%0.03
dust2B3014–1647%0.03
nukeA116–555%0.01
cacheC83–538%-0.01
ancientD60–60%-0.02
infernoD61–517%-0.00
anubisD62–433%-0.03

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (0% over 6). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

51,064Lifetime kills
0.98K/D · Top 50% of Blue band
4,350Matches
38.9%Match win rate
34.9%Headshot %
17.7%Shot accuracy · Top 10% of Blue band
3,864MVPs
856Hours (in match)
1,501Bombs planted
381Bombs defused

Most-used weapons

SSG 086,852
AK-476,487
AWP4,018
Knife2,128
SG 5531,916
MP71,709

Lifetime map wins

6,039dust2
1,429lake
1,424inferno
951safehouse
655ar_shoots
609nuke
268train
221vertigo

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

14.2%Headshot accuracy
38.6%Accuracy (enemy spotted)
40.3%Spray accuracy
76.4%Counter-strafing
8.5°Preaim
503msReaction time
61.4%T opening success
55.5%CT opening success
0.72Enemies flashed / flash
8.3%Flash assists
10.95HE damage / grenade
6.93Flashes / 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 14.1689% — below the 15% mark we flag

    Aim Training →
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.

0% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke9–13-0.019%30 Oct →
ancient10–130.018%30 Oct →
ancient10–13-0.0215%29 Oct →
mirage10–130.0813%29 Oct →
mirage13–60.039%29 Oct →
cache13–9-0.0618%29 Oct →
mirage13–50.1211%27 Oct →
cache7–130.0022%27 Oct →
nuke13–80.0910%27 Oct →
nuke11–130.0310%27 Oct →
inferno11–130.0618%26 Oct →
dust24–13-0.0233%26 Oct →
inferno8–13-0.034%25 Oct →
dust213–110.0927%25 Oct →
mirage13–70.0911%24 Oct →
dust213–80.0210%24 Oct →
anubis15–15-0.0317%23 Oct →
mirage11–13-0.078%23 Oct →
anubis13–8-0.0011%22 Oct →
cache16–14-0.008%22 Oct →
anubis13–11-0.0618%22 Oct →
mirage13–100.0313%22 Oct →
anubis10–130.0113%22 Oct →
ancient9–13-0.0410%21 Oct →
ancient7–13-0.0117%21 Oct →
cache4–13-0.0419%21 Oct →
dust210–130.0127%20 Oct →
nuke14–16-0.0413%20 Oct →
mirage13–80.0418%20 Oct →
mirage13–80.0912%20 Oct →
inferno11–130.0411%17 Oct →
dust213–6-0.0315%17 Oct →
mirage13–60.0311%16 Oct →
dust213–40.0225%16 Oct →
inferno13–90.0016%16 Oct →
nuke14–160.0614%15 Oct →
mirage10–13-0.0416%15 Oct →
nuke13–70.0911%15 Oct →
dust210–13-0.0618%13 Oct →
inferno8–13-0.0310%13 Oct →
mirage5–130.0420%13 Oct →
ancient11–130.0111%12 Oct →
anubis9–13-0.0411%12 Oct →
cache10–13-0.0729%8 Oct →
inferno7–13-0.057%8 Oct →
nuke13–11-0.063%8 Oct →
dust213–60.0123%8 Oct →
cache13–00.0510%8 Oct →
nuke13–50.0624%8 Oct →
dust213–100.015%7 Oct →
anubis11–13-0.0314%7 Oct →
nuke13–110.0313%7 Oct →
mirage15–150.046%7 Oct →
nuke13–11-0.0710%6 Oct →
mirage9–130.0418%6 Oct →
nuke4–13-0.0617%6 Oct →
mirage13–40.029%6 Oct →
cache9–130.0510%3 Oct →
dust210–13-0.0313%3 Oct →
mirage10–13-0.018%2 Oct →
mirage5–130.147%1 Oct →
mirage0–4-0.060%1 Oct →
dust22–110.0212%1 Oct →
mirage11–130.0110%1 Oct →
mirage13–80.038%1 Oct →
dust27–13-0.006%30 Sept →
mirage6–130.0314%30 Sept →
mirage10–13-0.0314%30 Sept →
dust29–130.0316%30 Sept →
dust27–13-0.0216%28 Sept →
mirage5–13-0.063%28 Sept →
dust213–30.105%28 Sept →
dust213–90.0512%25 Sept →
mirage13–9-0.0113%25 Sept →
dust22–13-0.0718%25 Sept →
dust211–130.014%24 Sept →
mirage8–130.0119%23 Sept →
mirage11–00.1028%23 Sept →
dust213–2-0.0119%23 Sept →
mirage13–90.1412%21 Sept →
dust23–130.0714%21 Sept →
cache6–130.0010%21 Sept →
mirage13–40.1110%18 Sept →
ancient5–13-0.047%18 Sept →
mirage4–7-0.0110%17 Sept →
dust210–130.0415%17 Sept →
mirage13–00.0916%17 Sept →
mirage13–30.0715%17 Sept →
mirage9–13-0.0122%17 Sept →
dust213–40.1219%16 Sept →
dust213–16-0.0414%16 Sept →
dust213–10.1410%16 Sept →
dust213–100.0817%15 Sept →
dust211–130.099%15 Sept →
dust213–80.0416%15 Sept →
mirage8–130.0418%15 Sept →
dust213–100.0717%14 Sept →
dust29–130.0414%14 Sept →
dust26–13-0.0417%14 Sept →
mirage13–60.0413%13 Sept →

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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