Pizza1551

Pizza1551 — CS2 Stats

NZ76561198854000230[U:1:893734502]Steam profile ↗✓ No bans

1,178Tracked matches39%Win rate2022Tracked since
1,741Hours in CS
CSDB Rating3.4 LearningSupport
Premier CS Rating15,514Purple band · top ~26.4% of ranked players (population est.)
FaceitLevel 2Top 97.9% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 10 Jun 2026 (129 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

15,514Peak Premier in tracked matches
40Days played since 2026-05-26

Premier CS Rating

  • At peak — 15,514
  • Next: Pink band at 20,000 — 4,486 to go
  • Reached: 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.

How this compares with the same rank

Median values for Level 2 among CSDB-tracked players (n=6,013), 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 playerLevel 2 medianLevel 3 medianvs Level 3
Headshot rate39.4%41.3%41.8%2.4% short
Shot accuracy9.1%12.7%12.2%3.1% short
Kill/death ratio0.830.950.980.15 short
Match win rate41.4%42.6%43.3%1.9% short

This profile sits below the typical Level 3 player on every metric we can compare.

Widest gap: Shot accuracy. That is the metric furthest from the Level 3 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGPizza1551FACEITLevel 2STANDINGTop 97.9% of rankedPREMIER15,514 · Purple 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

Aim46
Positioning31
Utility42

0–100 skill scores via Leetify.

Recent form

STEADY47–43–10Last 10047%Win rateLWLLWWLTWL

Last 10 vs previous 10: −10pp win rate · −0.01 avg rating · −2.3pp headshot accuracy · +16ms 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 632ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 17%
  • Avg reaction 645ms

Last 20

  • 9–9–2 · 45% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 19%
  • Avg reaction 637ms

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).

Aim4.6
Utility4.2
Positioning3.1
Opening Duels0.0

Limited 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

ZywOo

Plays most like ZywOo 87% 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. 615ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 69% 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

Aim4.6
Positioning3.1
Utility4.2
Mechanics4.3
Opening Duels0.0
Win Impact1.4

Composite 3.4/10 (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-0.02−0.01
first ⅓ avg -0.01 → last ⅓ avg -0.02
Reaction time614ms+17ms
first ⅓ avg 597ms → last ⅓ avg 614ms
Headshot accuracy18.1%+2.4%
first ⅓ avg 15.7% → last ⅓ avg 18.1%

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 · 13–10 · mirage, 31 May →
32%Best headshot accuracy · 13–8 · boulder, 9 Jul →
250msFastest reaction time · 2–13 · vertigo, 2 Jul →
13–1Biggest win · vertigo, 3 Jun →

Across the last 100 tracked matches.

Highlights

6Longest win streak
5–6In matches decided by ≤2 rounds

Map breakdown

vertigoBest map · 67% over 6dust2Weakest map · 29% over 21
MapGradePlayedRecordWin rateAvg rating
mirageB2513–1252%-0.01
cacheB2210–1245%-0.02
dust2D216–1529%-0.03
infernoA85–363%-0.04
nukeC83–538%-0.00
vertigoS64–267%-0.01
train—42–250%-0.01
ancient—21–150%-0.01
office—21–150%0.01
boulder—11–0100%-0.03
anubis—11–0100%-0.08

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (29% over 21). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

34,043Lifetime kills
0.83K/D
2,496Matches
41.4%Match win rate
39.4%Headshot %
9.1%Shot accuracy
2,567MVPs
1,741Hours (in match)
1,422Bombs planted
471Bombs defused

Most-used weapons

Lifetime map wins

4,305dust2
2,786inferno
2,057nuke
444vertigo
175train
110office
3italy
3cbble

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

Faceit stats

Combat

31Matches
39%Win rate
0.89Avg K/D
—ADR
40%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
2Longest win streak

Recent Faceit resultsLLLWW

MapMatchesWin rateAvg K/DAvg kills
Mirage862%1.1416.1
Inferno425%0.619.0
Nuke3100%1.0515.3
Overpass333%0.9112.7
Vertigo30%0.9813.3
Ancient1100%0.829.0

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

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

18.4%Headshot accuracy
29.3%Accuracy (enemy spotted)
28.2%Spray accuracy
69.4%Counter-strafing
9.2°Preaim
615msReaction time
24.0%T opening success
24.5%CT opening success
0.61Enemies flashed / flash
6.0%Flash assists
10.63HE damage / grenade
3.08Flashes / 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. Grenades & Utility

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 3.0773 — below the 4 mark we flag

    Grenade Lineups →
  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 24.0336% — below the 40% mark we flag

Spend your practice time on Dust 2

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

29% win rate across 21 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage6–13-0.1021%16 Oct →
dust213–7-0.0523%15 Oct →
dust23–13-0.0223%15 Oct →
inferno11–13-0.0116%15 Oct →
mirage13–5-0.0416%12 Oct →
ancient13–60.0117%12 Oct →
train8–130.0026%11 Oct →
cache12–12-0.0211%11 Oct →
mirage13–5-0.0513%8 Oct →
dust28–130.018%8 Oct →
inferno13–5-0.0622%15 Jul →
mirage13–6-0.0212%13 Jul →
mirage7–130.0521%13 Jul →
dust27–1-0.0717%13 Jul →
boulder13–8-0.0332%9 Jul →
office8–13-0.0223%8 Jul →
cache13–6-0.0410%8 Jul →
cache11–130.0116%7 Jul →
cache11–130.0619%6 Jul →
dust212–12-0.0126%5 Jul →
mirage8–130.0412%2 Jul →
dust213–9-0.0417%2 Jul →
vertigo2–13-0.116%2 Jul →
cache7–13-0.0115%1 Jul →
mirage13–9-0.0823%1 Jul →
nuke10–13-0.0120%28 Jun →
cache7–130.0528%28 Jun →
inferno4–13-0.0910%28 Jun →
dust26–13-0.0126%27 Jun →
mirage5–13-0.0220%27 Jun →
dust212–120.0716%26 Jun →
dust213–30.0016%26 Jun →
dust23–13-0.0316%26 Jun →
dust22–13-0.0325%23 Jun →
cache12–12-0.0218%22 Jun →
dust27–13-0.0118%22 Jun →
mirage12–12-0.0527%22 Jun →
nuke13–10-0.0614%22 Jun →
inferno7–13-0.0610%21 Jun →
dust213–110.0125%21 Jun →
cache12–120.019%20 Jun →
nuke13–6-0.0116%20 Jun →
dust211–13-0.0512%20 Jun →
nuke7–13-0.0515%20 Jun →
train13–6-0.0711%20 Jun →
mirage12–12-0.0421%19 Jun →
mirage0–130.0128%19 Jun →
cache8–13-0.0317%19 Jun →
dust25–13-0.0613%18 Jun →
cache13–100.0119%12 Jun →
train6–9-0.0217%12 Jun →
mirage13–10-0.0812%12 Jun →
dust29–13-0.0714%12 Jun →
anubis13–9-0.084%12 Jun →
mirage13–100.0615%11 Jun →
cache13–8-0.015%11 Jun →
dust213–9-0.0523%11 Jun →
mirage13–30.0723%11 Jun →
inferno13–9-0.063%10 Jun →
nuke12–120.0419%10 Jun →
nuke13–70.0715%10 Jun →
cache13–11-0.096%10 Jun →
ancient6–13-0.049%10 Jun →
vertigo13–7-0.0116%9 Jun →
vertigo13–50.049%9 Jun →
vertigo13–110.0615%8 Jun →
cache13–7-0.090%8 Jun →
inferno13–10-0.1011%8 Jun →
cache4–13-0.0916%8 Jun →
cache13–30.0216%8 Jun →
mirage10–13-0.069%8 Jun →
train13–60.0524%7 Jun →
vertigo6–13-0.0811%7 Jun →
office13–60.0313%7 Jun →
cache13–50.0225%6 Jun →
inferno13–50.0719%6 Jun →
cache12–12-0.0315%5 Jun →
dust27–130.0016%4 Jun →
mirage13–30.0924%3 Jun →
vertigo13–10.0416%3 Jun →
mirage8–13-0.0812%3 Jun →
mirage10–13-0.0314%1 Jun →
nuke2–2-0.010%1 Jun →
cache12–12-0.0512%1 Jun →
inferno13–110.0120%1 Jun →
cache8–13-0.0016%31 May →
nuke5–90.0019%31 May →
mirage13–100.1022%31 May →
cache13–11-0.0217%30 May →
cache13–10-0.0020%30 May →
mirage13–100.0011%30 May →
cache13–9-0.0015%29 May →
mirage10–130.0320%28 May →
mirage13–70.0323%28 May →
dust210–13-0.0518%28 May →
mirage13–90.0516%28 May →
mirage13–10-0.0714%27 May →
mirage11–13-0.0414%27 May →
dust24–13-0.0413%27 May →
dust22–13-0.077%26 May →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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