Pasta

Pasta — CS2 Stats

76561198379644532[U:1:419378804]Steam profile ↗✓ No bans

372Tracked matches30%Win rate2024Tracked since
CSDB Rating3.9 LearningSupport
Premier CS Rating6,730Light Blue band · top ~70.5% of ranked players (population est.)
WingmanLegendary Eagle Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 2 Nov 2026 (yesterday). Ranks are recorded once per day this page is viewed.

−263Premier CS Rating · 6,993 → 6,730

Rating over time

Premier CS Rating: 6,730 -7,945 30 Aug – 3 Nov · 32 days played
6,73018,128peak 18,12830 Aug3 Nov
18,349Peak Premier in tracked matches
30Days played since 2026-08-30

Premier CS Rating

  • 11,398 below peak (18,128)
  • -10,942 over 30 days · declining
  • Next: Blue band at 10,000 — 3,270 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-09-20
  • Blue band first seen 2026-08-30

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

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CSDB.GGPastaPREMIER6,730 · Light Blue bandcsdb.gg/stats

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Performance scores

Aim46
Positioning42
Utility54

0–100 skill scores via Leetify.

Recent form

COLD43–56–1Last 10043%Win rateLLWLLLLWLW

Last 10 vs previous 10: +10pp win rate · +0.02 avg rating · −1.7pp headshot accuracy · +0ms 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

  • 1–4 · 20% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 12%
  • Avg reaction 564ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 11%
  • Avg reaction 573ms

Last 20

  • 5–15 · 25% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 12%
  • Avg reaction 573ms

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 (+1.5 against its own average).

Aim4.6
Utility5.4
Positioning4.2
Opening Duels2.1

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

Twistzz

Plays most like Twistzz 78% 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. 567ms 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

Aim4.6
Positioning4.2
Utility5.4
Mechanics5.5
Opening Duels4.7
Win Impact0.0

Composite 3.9/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.02
first ⅓ avg 0.01 → last ⅓ avg -0.01
Reaction time565ms+43ms
first ⅓ avg 522ms → last ⅓ avg 565ms
Headshot accuracy14.2%−0.8%
first ⅓ avg 15.0% → last ⅓ avg 14.2%

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

0.18Best match rating · 11–0 · nuke, 14 Sept →
33%Best headshot accuracy · 13–11 · ancient, 20 Oct →
359msFastest reaction time · 13–6 · inferno, 19 Oct →
13–1Biggest win · ancient, 14 Sept →

Across the last 100 tracked matches.

Highlights

6Longest win streak
L2Current streak
6–10In matches decided by ≤2 rounds
11Overtime games

Map breakdown

nukeBest map · 56% over 18anubisWeakest map · 20% over 10
MapGradePlayedRecordWin rateAvg rating
nukeA1810–856%0.01
dust2C156–940%-0.00
infernoD155–1033%-0.02
ancientB147–750%0.02
mirageC135–838%-0.01
cacheB126–650%-0.01
anubisD102–820%-0.02
train—32–167%0.00

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (20% over 10). 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.

13.9%Headshot accuracy
30.0%Accuracy (enemy spotted)
29.2%Spray accuracy
74.6%Counter-strafing
10.8°Preaim
567msReaction time
53.1%T opening success
44.8%CT opening success
0.68Enemies flashed / flash
12.1%Flash assists
11.53HE damage / grenade
4.66Flashes / 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 13.9477% — below the 15% mark we flag

    Aim Training →
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.

20% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage3–13-0.039%3 Nov →
mirage12–16-0.0310%3 Nov →
dust213–60.0317%3 Nov →
inferno10–13-0.0015%2 Nov →
cache11–130.0111%2 Nov →
nuke9–13-0.0512%2 Nov →
ancient11–130.046%1 Nov →
mirage13–50.1412%1 Nov →
cache5–13-0.0418%1 Nov →
nuke13–11-0.035%1 Nov →
anubis5–130.0812%31 Oct →
ancient8–13-0.0712%30 Oct →
mirage11–13-0.045%30 Oct →
anubis10–13-0.0612%30 Oct →
dust212–160.0019%30 Oct →
dust213–60.0110%29 Oct →
cache7–13-0.028%28 Oct →
ancient7–13-0.0215%28 Oct →
nuke13–50.0113%28 Oct →
dust25–13-0.0724%28 Oct →
inferno8–13-0.0513%27 Oct →
mirage13–10-0.0413%26 Oct →
ancient13–30.1715%26 Oct →
nuke12–16-0.0221%26 Oct →
mirage5–13-0.0715%26 Oct →
cache13–10-0.0417%26 Oct →
inferno13–9-0.0519%25 Oct →
nuke1–13-0.0530%25 Oct →
inferno13–16-0.0318%25 Oct →
anubis11–13-0.0319%25 Oct →
dust26–13-0.1010%24 Oct →
cache13–40.0317%24 Oct →
dust210–130.0219%23 Oct →
cache13–70.1011%23 Oct →
nuke13–10-0.1021%23 Oct →
nuke10–13-0.0015%23 Oct →
nuke12–16-0.0221%23 Oct →
anubis5–13-0.0417%23 Oct →
anubis13–90.048%23 Oct →
inferno13–60.1121%23 Oct →
cache11–13-0.047%23 Oct →
dust214–160.0713%23 Oct →
inferno13–7-0.0513%22 Oct →
nuke9–13-0.096%22 Oct →
inferno11–13-0.0315%21 Oct →
cache9–13-0.017%21 Oct →
nuke11–130.0217%21 Oct →
cache5–13-0.0014%21 Oct →
anubis6–13-0.0210%21 Oct →
inferno9–130.0111%21 Oct →
ancient13–11-0.0533%20 Oct →
ancient4–80.0513%20 Oct →
anubis13–20.0422%20 Oct →
inferno7–13-0.0730%20 Oct →
mirage8–13-0.0720%20 Oct →
nuke13–110.1014%20 Oct →
inferno13–6-0.0121%19 Oct →
ancient7–13-0.0311%19 Oct →
dust21–13-0.0015%19 Oct →
inferno7–13-0.0713%19 Oct →
ancient8–20.0911%19 Oct →
mirage13–80.0918%19 Oct →
ancient10–13-0.0613%18 Oct →
anubis7–12-0.100%18 Oct →
inferno13–8-0.0325%18 Oct →
dust21–11-0.0910%17 Oct →
nuke8–130.0012%16 Oct →
inferno2–13-0.0912%15 Oct →
train9–13-0.0413%15 Oct →
ancient13–7-0.0112%15 Oct →
ancient11–130.0217%15 Oct →
mirage3–13-0.0418%15 Oct →
dust23–13-0.0525%15 Oct →
dust25–13-0.0415%15 Oct →
dust213–110.0128%14 Oct →
mirage10–13-0.017%13 Oct →
anubis1–13-0.080%11 Oct →
nuke13–70.0814%11 Oct →
mirage13–70.0414%8 Oct →
train13–80.0312%8 Oct →
train13–80.0118%8 Oct →
nuke16–140.0718%1 Oct →
nuke13–50.0527%28 Sept →
inferno15–150.0312%21 Sept →
nuke16–120.0616%21 Sept →
ancient13–60.0016%21 Sept →
dust213–5-0.018%17 Sept →
ancient16–130.0018%17 Sept →
cache13–11-0.055%17 Sept →
anubis14–16-0.0314%16 Sept →
cache13–40.0110%16 Sept →
mirage6–13-0.0416%16 Sept →
nuke13–4-0.0211%16 Sept →
mirage13–8-0.0311%16 Sept →
dust213–90.0616%16 Sept →
inferno6–130.0214%14 Sept →
cache13–4-0.0115%14 Sept →
nuke11–00.1826%14 Sept →
dust213–40.1018%14 Sept →
ancient13–10.0920%14 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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