Nutter Butter eSports Player

Nutter Butter eSports Player — CS2 Stats

76561198280817834[U:1:320552106]Steam profile ↗✓ No bans

267Tracked matches58%Win rate2023Tracked since
291Hours in CS
CSDB Rating4.6 DevelopingPositional Player
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 15 Sep 2026 (3 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 267 tracked matches. Play, then come back: the next observation lands here.

Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 34 days played since 27 May 2026. Come back after the next session and the change shows above.

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Rating over time

Premier CS Rating: 6,887 -173 28 May30 Jun · 2 days played
6,8877,060peak 7,06028 May30 Jun
7,060Peak Premier in tracked matches
34Days played since 2026-05-27

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

Performance scores

Aim53
Positioning48
Utility27

0–100 skill scores via Leetify.

Recent form

HOT583210Last 10058%Win rateLLWWWTWWWW

Last 10 vs previous 10: +30pp win rate · +0.03 avg rating · −1.5pp headshot accuracy · +6ms reaction

Win rate up 30pp 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

  • 32 · 60% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 12%
  • Avg reaction 555ms

Last 10

  • 721 · 70% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 11%
  • Avg reaction 584ms

Last 20

  • 1172 · 55% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 11%
  • Avg reaction 580ms

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 PlayerPositioning stands above the rest of this profile (+2.1 against its own average).

Aim5.3
Utility2.7
Positioning4.8
Opening Duels0.5

Strong CT-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

NiKo

Plays most like NiKo 81% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower aim profile; lower opening-duel success.

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 40% on CT to 22% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 599ms 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

Aim5.3
Positioning4.8
Utility2.7
Mechanics5.3
Opening Duels1.2
Win Impact7.6

Composite 4.6/10 (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-0.01−0.01
first ⅓ avg 0.00 → last ⅓ avg -0.01
Reaction time592ms+18ms
first ⅓ avg 574ms → last ⅓ avg 592ms
Headshot accuracy12.0%−0.1%
first ⅓ avg 12.1% → last ⅓ avg 12.0%

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

0.10Best match rating · 13–11 · vertigo, 1 Jul
35%Best headshot accuracy · 5–9 · vertigo, 11 Jun
391msFastest reaction time · 13–5 · dust2, 27 Jun
13–2Biggest win · anubis, 14 Jul

Across the last 100 tracked matches.

Highlights

7Longest win streak
L2Current streak
67In matches decided by ≤2 rounds
1Overtime games

Map breakdown

ancientBest map · 86% over 7infernoWeakest map · 30% over 10
MapGradePlayedRecordWin rateAvg rating
trainA1610663%0.01
nukeA138562%0.00
vertigoS119282%0.01
anubisB105550%-0.00
infernoD103730%-0.03
dust2B84450%-0.00
cacheA85363%0.00
ancientS76186%-0.01
overpassS64267%0.03
officeC52340%0.05
mirage41325%-0.02
italy110100%0.04
poseidon1010%-0.13

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (30% over 10). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

12,689Lifetime kills
0.86K/D
1,064Matches
39.4%Match win rate
29.7%Headshot %
10.2%Shot accuracy
1,027MVPs
291Hours (in match)
871Bombs planted
129Bombs defused

Most-used weapons

Lifetime map wins

785dust2
720nuke
643inferno
492office
383train
327vertigo
143italy
50assault

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.

11.8%Headshot accuracy
35.0%Accuracy (enemy spotted)
36.7%Spray accuracy
74.1%Counter-strafing
10.8°Preaim
599msReaction time
21.9%T opening success
40.0%CT opening success
0.34Enemies flashed / flash
3.1%Flash assists
4.98HE damage / grenade
3.11Flashes / 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 11.7586% — 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 0.3442 — 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 21.9389% — below the 40% mark we flag

Spend your practice time on Inferno

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

30% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
anubis1–13-0.0014%1 Aug
office11–13-0.0111%1 Aug
ancient13–50.0610%1 Aug
italy11–30.047%23 Jul
vertigo13–80.0119%23 Jul
anubis12–120.058%22 Jul
train13–50.0713%19 Jul
nuke13–5-0.018%19 Jul
anubis13–10-0.087%19 Jul
nuke13–7-0.039%16 Jul
inferno7–13-0.0415%16 Jul
inferno6–13-0.045%14 Jul
nuke13–110.058%14 Jul
dust210–13-0.0317%14 Jul
anubis13–2-0.0511%14 Jul
cache12–12-0.0014%14 Jul
ancient11–13-0.0715%12 Jul
ancient13–70.017%12 Jul
dust213–30.0222%12 Jul
train8–13-0.066%12 Jul
inferno13–10-0.0312%12 Jul
nuke9–13-0.0123%9 Jul
cache6–130.0017%9 Jul
mirage2–13-0.0811%9 Jul
inferno12–120.0210%9 Jul
dust213–60.069%9 Jul
vertigo12–12-0.0513%8 Jul
anubis13–7-0.024%8 Jul
train9–13-0.0613%8 Jul
nuke13–11-0.0114%5 Jul
cache13–10-0.0510%5 Jul
ancient13–5-0.0618%5 Jul
overpass13–60.0316%4 Jul
vertigo13–20.069%4 Jul
mirage6–0-0.0217%4 Jul
nuke5–130.0110%4 Jul
train13–70.0221%4 Jul
train13–30.0616%3 Jul
cache13–40.0215%3 Jul
office12–60.0810%3 Jul
overpass13–50.0813%3 Jul
vertigo13–110.0013%3 Jul
anubis13–100.0314%3 Jul
nuke12–12-0.049%3 Jul
inferno1–13-0.049%2 Jul
train11–1-0.027%2 Jul
train12–120.0310%1 Jul
office13–50.0311%1 Jul
vertigo13–110.1017%1 Jul
vertigo13–90.0112%30 Jun
inferno13–16-0.074%30 Jun
dust213–70.0110%30 Jun
overpass11–13-0.0217%30 Jun
nuke13–6-0.0219%30 Jun
vertigo13–60.0716%29 Jun
inferno8–130.0215%29 Jun
inferno13–11-0.039%27 Jun
dust213–5-0.028%27 Jun
mirage9–13-0.0016%27 Jun
nuke13–50.047%26 Jun
anubis10–13-0.0013%25 Jun
nuke13–70.059%25 Jun
ancient13–11-0.0510%25 Jun
inferno13–6-0.0012%25 Jun
office12–120.0811%25 Jun
cache5–13-0.078%21 Jun
mirage12–120.0111%21 Jun
overpass13–50.0912%21 Jun
train13–4-0.0311%21 Jun
dust22–13-0.0411%20 Jun
train12–12-0.038%20 Jun
train10–130.0114%20 Jun
train13–30.0414%19 Jun
train13–50.0814%18 Jun
nuke13–40.0514%14 Jun
anubis11–13-0.017%11 Jun
train13–6-0.0212%11 Jun
vertigo5–9-0.1535%11 Jun
inferno2–9-0.064%11 Jun
dust211–130.0216%10 Jun
train11–13-0.055%10 Jun
cache13–20.024%10 Jun
vertigo9–4-0.0710%9 Jun
poseidon5–9-0.1311%9 Jun
cache13–70.0710%8 Jun
train13–7-0.028%7 Jun
train13–40.089%7 Jun
vertigo13–80.069%7 Jun
vertigo13–50.0217%7 Jun
overpass5–13-0.059%5 Jun
ancient13–100.028%4 Jun
cache13–20.0414%4 Jun
office7–130.058%4 Jun
nuke9–13-0.0413%31 May
nuke11–130.0115%28 May
overpass13–30.0710%28 May
ancient13–30.0017%28 May
dust26–13-0.0224%28 May
anubis12–120.047%27 May
anubis13–60.0018%27 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 →