Parmesan

Parmesan — CS2 Stats

US76561198125086761[U:1:164821033]Steam profile ↗✓ No bans

1,569Tracked matches37%Win rate2022Tracked since
1,393Hours in CS
CSDB Rating3.6 LearningSupport
Premier CS Rating12,964Blue band · top ~39.2% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 6 Sep 2026 (17 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 1,569 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. 35 days played since 9 Jun 2026. Come back after the next session and the change shows above.

Is this you? Sign in with Steam to claim it and connect match tracking →

Rating over time

Premier CS Rating: 12,964 +755 9 Jun6 Sept · 29 days played
12,20916,046peak 16,0469 Jun6 Sept
16,131Peak Premier in tracked matches
35Days played since 2026-06-09

Premier CS Rating

  • 3,082 below peak (16,046)
  • -2,776 over 30 days · declining
  • +755 over 90 days
  • Next: Purple band at 15,000 2,036 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Blue band first seen 2026-08-28
  • Light Blue band first seen 2026-08-28

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

Compare periods

Last 30 days vs previous 30

No matches recorded between 28 Aug 2026 and 23 Sep 2026.

Measured 28 Aug 202623 Sep 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Blue band among CSDB-tracked players (n=21,222), 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 playerBlue band medianPurple band medianvs Purple band
Headshot rate29.4%41.9%44.3%14.9% short
Shot accuracy10.3%9.6%11.8%1.6% short
Kill/death ratio0.920.981.030.11 short
Match win rate43.4%43.8%45.2%1.8% short

This profile sits below the typical Purple band player on every metric we can compare.

Widest gap: Headshot rate. That is the metric furthest from the Purple band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGParmesanPREMIER12,964 · Blue bandcsdb.gg/stats

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Performance scores

Aim36
Positioning45
Utility61

0–100 skill scores via Leetify.

Recent form

STEADY47521Last 10047%Win rateWLLLLWWLWL

Last 10 vs previous 10: +10pp win rate · +0.02 avg rating · +1.6pp 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

  • 14 · 20% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 13%
  • Avg reaction 527ms

Last 10

  • 46 · 40% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 13%
  • Avg reaction 539ms

Last 20

  • 713 · 35% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 13%
  • Avg reaction 547ms

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: SupportUtility contribution stands above the rest of this profile (+1.5 against its own average).

Aim3.6
Utility6.1
Positioning4.5
Opening Duels3.3

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

jL

Plays most like jL 63% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower positioning profile; 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 52% on CT to 28% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 565ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 65% 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

Aim3.6
Positioning4.5
Utility6.1
Mechanics3.4
Opening Duels2.8
Win Impact0.6

Composite 3.6/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01+0.01
first ⅓ avg -0.02 → last ⅓ avg -0.01
Reaction time569ms−9ms
first ⅓ avg 578ms → last ⅓ avg 569ms
Headshot accuracy12.5%−0.9%
first ⅓ avg 13.4% → last ⅓ avg 12.5%

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

0.11Best match rating · 13–7 · dust2, 10 Jun
21%Best headshot accuracy · 13–6 · mirage, 10 Jun
375msFastest reaction time · 13–4 · ancient, 22 Jul
13–1Biggest win · dust2, 27 Jul

Across the last 100 tracked matches.

Highlights

6Longest win streak
49In matches decided by ≤2 rounds
15Overtime games

Map breakdown

dust2Best map · 79% over 14ancientWeakest map · 27% over 15
MapGradePlayedRecordWin rateAvg rating
nukeC2291341%-0.02
ancientD1541127%-0.03
dust2S1411379%0.01
cacheC146843%-0.05
mirageB147750%0.00
infernoA116555%0.00
anubisC94544%0.01
overpass1010%-0.06

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (27% over 15). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

62,363Lifetime kills
0.92K/D
3,501Matches
43.4%Match win rate
29.4%Headshot %
10.3%Shot accuracy · Top 50% of Blue band
6,546MVPs
1,393Hours (in match)
3,211Bombs planted
691Bombs defused

Most-used weapons

P9016,823
AWP12,807
AK-475,470
MP72,161
P2501,534
Tec-91,305
SSG 081,140

Lifetime map wins

19,207dust2
2,931inferno
2,205nuke
1,275vertigo
360train
242lake
103bank
98safehouse

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.

12.7%Headshot accuracy
32.8%Accuracy (enemy spotted)
30.7%Spray accuracy
65.4%Counter-strafing
12.8°Preaim
565msReaction time
28.4%T opening success
52.2%CT opening success
0.57Enemies flashed / flash
3.6%Flash assists
11.96HE damage / grenade
13.56Flashes / 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 12.8152° — 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 12.6615% — below the 15% mark we flag

    Aim Training
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.

27% win rate across 15 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategyAncient grenade lineups

Recent matches

MapScoreRatingHS%Date
anubis13–100.0514%21 Aug
ancient5–13-0.070%20 Aug
nuke9–130.0319%20 Aug
nuke6–13-0.0310%20 Aug
nuke7–130.0421%19 Aug
dust213–100.0220%19 Aug
inferno13–20.0313%19 Aug
anubis6–13-0.018%18 Aug
anubis13–90.0411%17 Aug
inferno9–13-0.0516%17 Aug
nuke13–80.056%17 Aug
cache13–6-0.0311%17 Aug
mirage13–9-0.0319%17 Aug
cache9–13-0.049%16 Aug
mirage12–16-0.0117%12 Aug
cache10–13-0.026%11 Aug
cache12–16-0.0115%11 Aug
mirage11–13-0.0112%10 Aug
nuke10–13-0.0114%10 Aug
anubis5–13-0.008%10 Aug
nuke9–13-0.0714%9 Aug
ancient12–16-0.0419%8 Aug
nuke5–13-0.047%8 Aug
mirage13–3-0.0010%8 Aug
ancient6–13-0.069%7 Aug
inferno13–30.029%7 Aug
ancient13–160.038%7 Aug
dust213–80.0118%6 Aug
cache1–13-0.0710%6 Aug
dust213–7-0.0116%6 Aug
mirage11–13-0.0319%6 Aug
dust213–100.108%5 Aug
inferno13–60.0317%5 Aug
ancient13–100.025%5 Aug
dust213–90.0212%5 Aug
anubis13–7-0.055%5 Aug
cache16–14-0.0610%5 Aug
ancient10–13-0.0317%5 Aug
cache15–15-0.0315%4 Aug
mirage7–13-0.057%3 Aug
nuke13–60.038%3 Aug
nuke13–3-0.0018%3 Aug
inferno4–13-0.022%2 Aug
ancient9–13-0.039%2 Aug
nuke8–13-0.1014%1 Aug
mirage5–13-0.0113%1 Aug
ancient13–16-0.037%31 Jul
nuke13–5-0.064%31 Jul
mirage16–130.057%31 Jul
dust216–130.0115%31 Jul
dust21–13-0.074%31 Jul
dust213–5-0.0012%31 Jul
nuke5–13-0.0715%30 Jul
anubis13–80.0616%30 Jul
nuke13–11-0.046%30 Jul
anubis12–16-0.0218%30 Jul
nuke13–10-0.0218%30 Jul
ancient11–13-0.0113%30 Jul
anubis11–130.0119%28 Jul
mirage13–80.0015%28 Jul
ancient13–9-0.0111%28 Jul
dust213–60.016%27 Jul
mirage13–70.0513%27 Jul
dust213–10.0420%27 Jul
mirage10–13-0.0215%27 Jul
nuke13–8-0.0213%26 Jul
dust213–9-0.036%26 Jul
inferno13–90.0221%25 Jul
ancient13–100.0210%25 Jul
cache5–13-0.075%23 Jul
inferno13–10-0.0013%23 Jul
cache11–13-0.0515%22 Jul
dust210–13-0.0213%22 Jul
cache13–100.0118%22 Jul
inferno14–160.0711%22 Jul
ancient13–40.0011%22 Jul
dust213–160.0211%21 Jul
nuke6–13-0.0220%21 Jul
nuke16–14-0.0112%21 Jul
anubis12–160.0112%20 Jul
cache12–16-0.1016%20 Jul
nuke4–13-0.069%20 Jul
cache13–7-0.047%11 Jul
nuke10–13-0.1212%10 Jul
nuke5–13-0.0319%10 Jul
cache13–10-0.066%9 Jul
cache13–1-0.085%9 Jul
ancient8–13-0.0316%4 Jul
inferno11–13-0.0616%4 Jul
nuke11–130.0516%4 Jul
mirage1–13-0.0313%4 Jul
ancient11–13-0.0719%15 Jun
nuke13–8-0.0313%15 Jun
inferno13–11-0.0417%10 Jun
ancient10–13-0.0811%10 Jun
mirage13–5-0.019%10 Jun
mirage13–60.1021%10 Jun
dust213–70.1119%10 Jun
inferno9–130.0213%9 Jun
overpass8–13-0.0614%9 Jun

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 →