Bananaman

Bananaman — CS2 Stats

76561199389650785[U:1:1429385057]Steam profile ↗✓ No bans

889Tracked matches45%Win rate2022Tracked since
CSDB Rating6.2 SolidAll-Rounder
Premier CS Rating19,890Top 50% of 212,133 CSDB-tracked playersPurple band · top ~8.9% of ranked players (population est.)
CSDB Leaderboard#87236 of 258963 tracked
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 24 Feb 2026 (249 days ago). 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: 19,890 +3,363 28 Aug – 24 Feb · 24 days played
16,52720,000peak 20,00028 Aug24 Feb
20,119Peak Premier in tracked matches
38Days played since 2025-07-26

Premier CS Rating

  • 110 below peak (20,000)
  • -110 over 30 days · steady
  • +695 over 90 days
  • Next: Pink band at 20,000 — 110 to go
  • Reached: Pink band · Purple band · Blue band · Light Blue band

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

Share this profile

CSDB.GGBananamanPREMIER19,890 · Purple bandcsdb.gg/stats

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Performance scores

Aim66
Positioning70
Utility74

0–100 skill scores via Leetify.

Recent form

STEADY45–52–3Last 10045%Win rateLLWWLLWWLW

Last 10 vs previous 10: +10pp win rate · +0.01 avg rating · +1.1pp headshot accuracy · −11ms 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 0.04
  • Avg headshot accuracy 20%
  • Avg reaction 544ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 17%
  • Avg reaction 582ms

Last 20

  • 9–11 · 45% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 16%
  • Avg reaction 588ms

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: All-Rounder — No style dimension stands clear of the others in this profile.

Aim6.6
Utility7.4
Positioning7.0
Opening Duels6.4

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

Twistzz

Plays most like Twistzz 73% playstyle similarity

Most alike: opening-duel success, 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

CT openings. 67% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

T-side openings. Opening success drops from 67% on CT to 43% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 576ms 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

Aim6.6
Positioning7.0
Utility7.4
Mechanics5.0
Opening Duels6.2
Win Impact3.3

Composite 6.2/10 (Solid), 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 rating0.03−0.00
first ⅓ avg 0.03 → last ⅓ avg 0.03
Reaction time575ms−15ms
first ⅓ avg 590ms → last ⅓ avg 575ms
Headshot accuracy16.2%−3.0%
first ⅓ avg 19.2% → last ⅓ avg 16.2%

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

0.24Best match rating · 2–0 · overpass, 1 Aug →
43%Best headshot accuracy · 2–0 · overpass, 1 Aug →
453msFastest reaction time · 13–11 · ancient, 8 Feb →
13–1Biggest win · train, 7 Sept →

Across the last 100 tracked matches.

Highlights

3Longest win streak
L2Current streak
10–12In matches decided by ≤2 rounds
13Overtime games

Map breakdown

infernoBest map · 54% over 26ancientWeakest map · 31% over 16
MapGradePlayedRecordWin rateAvg rating
infernoB2614–1254%0.04
ancientD165–1131%0.02
anubisC156–940%0.05
nukeB157–847%0.03
overpassB157–847%0.04
dust2C94–544%0.06
train—42–250%0.07

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (31% over 16). 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.

15.9%Headshot accuracy
36.3%Accuracy (enemy spotted)
36.0%Spray accuracy
72.6%Counter-strafing
9.4°Preaim
576msReaction time
42.7%T opening success
66.7%CT opening success
0.65Enemies flashed / flash
4.0%Flash assists
10.44HE damage / grenade
22.75Flashes / match

Recommended for you

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.

31% win rate across 16 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno11–130.1320%1 Aug →
dust27–130.0425%24 Feb →
anubis13–90.0118%18 Feb →
anubis13–100.0519%18 Feb →
dust213–16-0.0116%15 Feb →
nuke11–130.0118%10 Feb →
overpass13–90.0415%9 Feb →
inferno13–110.0411%9 Feb →
anubis8–13-0.0111%9 Feb →
inferno13–50.0511%9 Feb →
overpass16–140.018%9 Feb →
inferno13–90.0215%8 Feb →
nuke10–13-0.029%8 Feb →
ancient13–110.1015%8 Feb →
dust216–120.1124%8 Feb →
nuke6–13-0.0218%8 Feb →
overpass9–130.0113%2 Feb →
ancient11–130.0416%1 Feb →
anubis11–13-0.0021%1 Feb →
overpass9–13-0.0116%1 Feb →
anubis14–16-0.0116%1 Feb →
anubis5–130.0224%31 Jan →
anubis13–70.0813%31 Jan →
inferno13–90.1114%31 Jan →
nuke13–110.0624%31 Jan →
ancient3–13-0.0513%31 Jan →
inferno16–130.1013%31 Jan →
ancient15–150.1217%31 Jan →
nuke4–13-0.0119%31 Jan →
inferno7–13-0.036%30 Jan →
anubis13–70.0223%30 Jan →
overpass10–13-0.0028%30 Jan →
inferno13–100.048%30 Jan →
overpass8–130.0414%28 Jan →
inferno13–60.1315%28 Jan →
anubis8–130.0113%27 Jan →
overpass13–11-0.0217%27 Jan →
nuke6–20.0529%27 Jan →
ancient13–60.0923%26 Jan →
anubis11–130.1113%26 Jan →
anubis9–130.1615%26 Jan →
anubis9–130.1021%25 Jan →
anubis13–110.1217%25 Jan →
dust213–90.1227%24 Jan →
ancient10–130.0212%24 Jan →
anubis11–130.0414%24 Jan →
inferno13–60.0318%24 Jan →
nuke13–90.0213%18 Jan →
inferno11–130.0225%18 Jan →
ancient11–130.0222%18 Jan →
ancient8–13-0.0115%18 Jan →
dust213–80.0818%18 Jan →
ancient13–110.0114%17 Jan →
dust213–160.0526%16 Jan →
anubis13–80.0614%14 Jan →
nuke13–90.0916%14 Jan →
overpass10–130.0820%13 Jan →
train8–130.0517%13 Jan →
dust211–130.0319%13 Jan →
inferno13–100.0718%13 Jan →
ancient13–9-0.0020%13 Jan →
inferno9–130.0316%9 Jan →
ancient4–13-0.0521%9 Jan →
nuke15–150.0617%9 Jan →
dust211–130.0313%9 Jan →
overpass16–130.1727%4 Jan →
inferno9–13-0.0011%4 Jan →
overpass10–130.0125%4 Jan →
inferno14–160.0118%3 Jan →
ancient7–13-0.0114%3 Jan →
inferno5–130.0321%3 Jan →
inferno5–13-0.0729%3 Jan →
ancient6–13-0.0012%29 Dec →
inferno13–80.0911%29 Dec →
inferno13–80.1823%29 Dec →
train15–150.0620%28 Dec →
nuke5–130.0523%28 Dec →
nuke13–30.1035%28 Dec →
overpass10–130.0010%25 Dec →
inferno5–13-0.0116%19 Dec →
overpass7–13-0.0519%19 Dec →
inferno16–130.0314%25 Nov →
dust213–70.0515%25 Nov →
ancient13–6-0.0215%29 Sept →
nuke12–160.0318%27 Sept →
overpass13–8-0.0115%27 Sept →
train13–10.1929%7 Sept →
inferno6–130.0222%7 Sept →
train13–9-0.0113%7 Sept →
inferno13–11-0.0116%6 Sept →
inferno13–80.0720%28 Aug →
nuke9–130.025%28 Aug →
inferno7–13-0.0525%5 Aug →
ancient3–13-0.0816%1 Aug →
inferno5–13-0.0224%1 Aug →
overpass2–00.2443%1 Aug →
nuke13–110.0326%1 Aug →
overpass13–80.0414%1 Aug →
ancient10–130.0919%28 Jul →
nuke13–60.0112%26 Jul →

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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