Banjo

Banjo — CS2 Stats

76561198084529192[U:1:124263464]Steam profile ↗✓ No bans

222Tracked matches37%Win rate2023Tracked since
CSDB Rating4.3 DevelopingSupport
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 15 Sep 2026 (30 days ago). Ranks are recorded once per day this page is viewed.

+5Tracked matches · now 222
−6.7ppWin rate · 43.3% → 36.7%

Rating over time

Premier CS Rating: 4,999 +645 11 Oct – 16 Jun · 27 days played
4,2706,083peak 6,08311 Oct16 Jun
6,314Peak Premier in tracked matches
66Days played since 2025-09-25

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

Performance scores

Aim43
Positioning44
Utility62

0–100 skill scores via Leetify.

Recent form

COLD41–53–6Last 10041%Win rateLLWLWWLLLL

Last 10 vs previous 10: −10pp win rate · +0.01 avg rating · −1.7pp headshot accuracy · −33ms 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

  • 2–3 · 40% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 9%
  • Avg reaction 714ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 11%
  • Avg reaction 636ms

Last 20

  • 7–13 · 35% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 12%
  • Avg reaction 652ms

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 (+1.8 against its own average).

Aim4.3
Utility6.2
Positioning4.4
Opening Duels2.7

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

NiKo

Plays most like NiKo 69% 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

Reaction time. 641ms 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

Aim4.3
Positioning4.4
Utility6.2
Mechanics6.1
Opening Duels2.2
Win Impact0.6

Composite 4.3/10 (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 rating-0.01−0.03
first ⅓ avg 0.02 → last ⅓ avg -0.01
Reaction time652ms−31ms
first ⅓ avg 683ms → last ⅓ avg 652ms
Headshot accuracy12.5%−1.2%
first ⅓ avg 13.7% → last ⅓ avg 12.5%

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

0.16Best match rating · 13–5 · overpass, 8 Jan →
29%Best headshot accuracy · 13–10 · inferno, 12 Oct →
438msFastest reaction time · 13–10 · mirage, 25 May →
13–2Biggest win · warden, 9 Apr →

Across the last 100 tracked matches.

Highlights

3Longest win streak
L2Current streak
5–8In matches decided by ≤2 rounds
16Overtime games

Map breakdown

infernoBest map · 57% over 23anubisWeakest map · 0% over 5
MapGradePlayedRecordWin rateAvg rating
infernoA2313–1057%0.01
dust2C187–1139%0.01
mirageB136–746%-0.01
nukeC114–736%0.02
overpassC114–736%0.01
cacheD72–529%-0.02
ancientD61–517%-0.01
anubisD50–50%-0.01
train—21–150%-0.01
vertigo—21–150%0.05
alpine—11–0100%0.01
warden—11–0100%0.11

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (0% over 5). Start with the 6 essential Anubis 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.

12.7%Headshot accuracy
28.8%Accuracy (enemy spotted)
31.3%Spray accuracy
77.2%Counter-strafing
9.5°Preaim
641msReaction time
39.7%T opening success
37.7%CT opening success
0.63Enemies flashed / flash
5.8%Flash assists
8.08HE damage / grenade
12.64Flashes / 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 12.7079% — below the 15% mark we flag

    Aim Training →
  2. 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 39.7019% — below the 40% mark we flag

Spend your practice time on Anubis

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 5 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage7–13-0.028%11 Oct →
cache10–130.059%9 Oct →
inferno13–40.0311%6 Oct →
nuke0–13-0.0613%5 Oct →
cache13–60.015%5 Oct →
cache13–110.0115%25 Aug →
mirage9–13-0.029%21 Aug →
dust24–130.0416%21 Aug →
cache2–13-0.0611%14 Aug →
cache13–16-0.0316%13 Aug →
dust29–13-0.0318%12 Aug →
cache7–13-0.0210%9 Jul →
inferno16–130.057%16 Jun →
ancient1–13-0.0713%15 Jun →
inferno13–40.0318%13 Jun →
dust20–13-0.0814%13 Jun →
inferno13–30.0314%4 Jun →
overpass11–130.0116%31 May →
anubis10–13-0.0514%28 May →
mirage13–10-0.014%25 May →
mirage11–130.0814%21 May →
dust25–13-0.0123%18 May →
mirage13–8-0.084%17 May →
cache11–13-0.0714%8 May →
overpass8–13-0.1125%7 May →
inferno16–13-0.036%30 Apr →
inferno8–13-0.0129%28 Apr →
inferno13–60.0913%27 Apr →
anubis5–13-0.024%23 Apr →
inferno13–7-0.0414%16 Apr →
overpass13–30.055%16 Apr →
ancient12–160.0110%13 Apr →
dust213–11-0.0112%13 Apr →
alpine13–60.019%9 Apr →
warden13–20.1115%9 Apr →
anubis15–15-0.0411%3 Apr →
nuke10–130.0820%30 Mar →
ancient3–13-0.0421%24 Mar →
dust25–130.0217%17 Mar →
anubis8–13-0.0116%17 Mar →
dust213–90.0211%16 Mar →
mirage13–10-0.0212%12 Mar →
anubis15–150.0513%6 Mar →
overpass8–130.0324%3 Mar →
overpass12–16-0.0224%25 Feb →
inferno10–13-0.0123%25 Feb →
inferno15–150.028%24 Feb →
dust216–130.0715%16 Feb →
nuke15–150.049%16 Feb →
dust213–40.0012%19 Jan →
train9–130.0014%12 Jan →
overpass13–50.1612%8 Jan →
dust21–9-0.0310%8 Jan →
mirage13–50.0512%4 Jan →
nuke13–90.0417%4 Jan →
vertigo10–130.015%22 Dec →
overpass13–100.028%16 Dec →
ancient16–14-0.048%16 Dec →
inferno10–13-0.074%16 Dec →
mirage7–13-0.019%12 Dec →
dust26–13-0.0120%10 Dec →
inferno9–10.038%10 Dec →
dust214–160.0312%25 Nov →
dust214–16-0.019%20 Nov →
inferno5–130.0116%20 Nov →
inferno7–13-0.0112%18 Nov →
dust24–13-0.029%18 Nov →
inferno13–80.0314%4 Nov →
overpass9–130.0711%4 Nov →
dust213–80.0711%3 Nov →
mirage10–130.0019%3 Nov →
inferno9–13-0.0318%1 Nov →
mirage11–13-0.0417%30 Oct →
nuke12–10.066%30 Oct →
ancient10–13-0.006%30 Oct →
nuke11–130.0220%29 Oct →
mirage7–13-0.0518%25 Oct →
overpass13–60.0015%25 Oct →
dust213–40.0223%24 Oct →
nuke13–2-0.023%24 Oct →
overpass6–13-0.0413%24 Oct →
mirage13–110.0012%24 Oct →
dust213–100.1213%21 Oct →
inferno13–40.1011%20 Oct →
nuke15–150.0916%20 Oct →
inferno10–130.016%17 Oct →
train16–14-0.0110%17 Oct →
inferno16–120.0316%16 Oct →
inferno13–20.0013%16 Oct →
ancient8–130.077%14 Oct →
inferno13–100.0429%12 Oct →
nuke13–6-0.0121%12 Oct →
overpass11–13-0.0014%12 Oct →
mirage13–80.0111%12 Oct →
nuke10–13-0.0211%11 Oct →
inferno6–130.0118%11 Oct →
inferno0–13-0.0719%11 Oct →
dust26–130.048%11 Oct →
nuke12–12-0.0414%25 Sept →
vertigo9–50.0810%25 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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