Mr. Nuts

Mr. Nuts — CS2 Stats

76561199090278533[U:1:1130012805]Steam profile ↗✓ No bans

479Tracked matches59%Win rate2024Tracked since
CSDB Rating3.5 LearningPositional Player
Ladder ranks via Leetify

Performance scores

Aim24
Positioning44
Utility41

0–100 skill scores via Leetify.

Recent form

COLD47–38–15Last 10047%Win rateTWLLLLLWLL

Last 10 vs previous 10: −50pp win rate · +0.00 avg rating · +3.4pp headshot accuracy · −28ms reaction

Win rate down 50pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (+0.00), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 1–3–1 · 20% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 15%
  • Avg reaction 664ms

Last 10

  • 2–7–1 · 20% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 13%
  • Avg reaction 648ms

Last 20

  • 9–8–3 · 45% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 11%
  • Avg reaction 662ms

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 (+1.5 against its own average).

Aim2.4
Utility4.1
Positioning4.4
Opening Duels0.2

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

iM

Plays most like iM 65% 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

T-side openings. Opening success drops from 43% on CT to 18% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 670ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 59% 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

Aim2.4
Positioning4.4
Utility4.1
Mechanics2.0
Opening Duels1.7
Win Impact8.1

Composite 3.5/10 (Learning), 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-0.03+0.02
first ⅓ avg -0.04 → last ⅓ avg -0.03
Reaction time672ms−15ms
first ⅓ avg 688ms → last ⅓ avg 672ms
Headshot accuracy12.3%−0.1%
first ⅓ avg 12.3% → last ⅓ avg 12.3%

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

0.13Best match rating · 13–4 · vertigo, 7 Aug →
32%Best headshot accuracy · 11–13 · office, 16 Aug →
453msFastest reaction time · 6–13 · anubis, 2 Sept →
13–2Biggest win · vertigo, 20 Sept →

Across the last 100 tracked matches.

Highlights

4Longest win streak
5–9In matches decided by ≤2 rounds
1Overtime games

Map breakdown

vertigoBest map · 65% over 37cacheWeakest map · 0% over 6
MapGradePlayedRecordWin rateAvg rating
vertigoS3724–1365%-0.02
nukeB2913–1645%-0.04
anubisD144–1029%-0.02
cacheD60–60%-0.04
officeD51–420%-0.07
inferno—22–0100%0.01
debris—11–0100%-0.01
ancient—10–10%-0.01
train—10–10%0.02
dust2—10–10%-0.08
shelter—11–0100%-0.04
fachwerk—10–10%-0.02
boulder—11–0100%-0.07

Across the last 100 tracked matches.

Skill profile

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

12.2%Headshot accuracy
31.2%Accuracy (enemy spotted)
35.0%Spray accuracy
59.0%Counter-strafing
12.5°Preaim
670msReaction time
17.5%T opening success
43.3%CT opening success
0.37Enemies flashed / flash
8.3%Flash assists
7.56HE damage / grenade
3.87Flashes / 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. Advanced Mechanics

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 12.4972° — above the 12° mark we flag

    Aim Training →
  2. 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 12.1766% — below the 15% mark we flag

    Aim Training →
  3. 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 0.373 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Cache

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.

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
vertigo12–12-0.0215%4 Nov →
nuke13–9-0.0317%4 Nov →
vertigo11–13-0.0513%30 Oct →
nuke11–13-0.0116%30 Oct →
vertigo4–130.0114%13 Oct →
vertigo11–13-0.0211%13 Oct →
nuke3–13-0.043%13 Oct →
vertigo13–80.0112%12 Oct →
nuke4–13-0.0313%12 Oct →
office8–13-0.0912%30 Sept →
vertigo13–3-0.052%30 Sept →
nuke13–9-0.067%30 Sept →
vertigo13–7-0.0420%29 Sept →
nuke13–9-0.0210%29 Sept →
vertigo10–13-0.096%28 Sept →
anubis13–40.0415%24 Sept →
vertigo13–9-0.0111%24 Sept →
nuke12–120.069%24 Sept →
vertigo12–12-0.0510%23 Sept →
nuke13–9-0.113%23 Sept →
cache7–13-0.0218%21 Sept →
anubis3–13-0.0618%21 Sept →
vertigo13–40.0518%21 Sept →
nuke13–3-0.0216%21 Sept →
nuke5–9-0.0711%20 Sept →
debris9–7-0.0115%20 Sept →
inferno9–50.0613%20 Sept →
nuke13–11-0.0414%20 Sept →
vertigo13–2-0.0711%20 Sept →
anubis9–13-0.0016%20 Sept →
vertigo13–7-0.0611%4 Sept →
nuke13–10-0.0315%4 Sept →
anubis13–20.0311%4 Sept →
anubis6–13-0.062%2 Sept →
nuke11–13-0.0516%2 Sept →
vertigo13–60.0211%2 Sept →
office11–13-0.0420%2 Sept →
ancient9–13-0.0110%19 Aug →
vertigo10–13-0.028%19 Aug →
vertigo13–20.0428%18 Aug →
nuke13–60.0213%18 Aug →
anubis6–13-0.0418%18 Aug →
nuke12–12-0.0419%18 Aug →
vertigo13–11-0.0420%18 Aug →
anubis13–7-0.0311%17 Aug →
vertigo10–13-0.0118%17 Aug →
nuke8–130.0220%17 Aug →
office11–13-0.1032%16 Aug →
vertigo13–30.0124%16 Aug →
anubis12–12-0.0327%13 Aug →
vertigo12–12-0.043%13 Aug →
train6–130.025%12 Aug →
vertigo13–8-0.058%12 Aug →
vertigo13–40.1318%7 Aug →
anubis12–120.0115%7 Aug →
vertigo13–10-0.018%7 Aug →
nuke8–13-0.0511%7 Aug →
vertigo11–13-0.0614%6 Aug →
nuke13–6-0.0212%6 Aug →
anubis11–13-0.0312%5 Aug →
vertigo13–80.0210%5 Aug →
nuke13–9-0.0511%5 Aug →
vertigo13–9-0.0221%5 Aug →
cache12–12-0.1013%1 Aug →
nuke13–7-0.027%1 Aug →
vertigo13–110.019%1 Aug →
vertigo13–3-0.0019%1 Aug →
nuke5–13-0.019%28 Jul →
cache15–15-0.0316%28 Jul →
nuke2–13-0.099%28 Jul →
nuke3–13-0.054%23 Jul →
vertigo13–8-0.0318%23 Jul →
anubis13–9-0.028%23 Jul →
dust25–13-0.083%22 Jul →
cache0–13-0.0225%22 Jul →
inferno13–6-0.043%22 Jul →
anubis11–13-0.0111%21 Jul →
vertigo13–7-0.057%21 Jul →
nuke8–13-0.0910%21 Jul →
vertigo13–9-0.0516%15 Jul →
nuke12–12-0.0613%15 Jul →
vertigo7–13-0.098%13 Jul →
nuke13–10-0.0120%13 Jul →
cache8–13-0.0317%13 Jul →
office12–12-0.0311%9 Jul →
vertigo13–8-0.0116%9 Jul →
shelter13–10-0.047%9 Jul →
fachwerk9–13-0.0218%9 Jul →
boulder13–10-0.0712%8 Jul →
nuke12–12-0.126%8 Jul →
vertigo10–13-0.029%8 Jul →
office13–3-0.0816%8 Jul →
nuke12–12-0.0911%7 Jul →
vertigo13–11-0.0612%7 Jul →
vertigo12–12-0.0710%30 Jun →
cache12–12-0.0419%30 Jun →
nuke13–30.0115%30 Jun →
vertigo13–5-0.027%25 Jun →
anubis7–13-0.0615%25 Jun →
anubis6–13-0.0229%23 Jun →

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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