Kressinator

Kressinator — CS2 Stats

DE76561199416881628[U:1:1456615900]Steam profile ↗✓ No bans

1,186Tracked matches43%Win rate2023Tracked since
963Hours in CS
CSDB Rating2.8 LearningPositional Player
Premier CS Rating5,456Light Blue band · top ~76.6% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 30 Sep 2026 (yesterday). 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

Premier CS Rating: 5,456 -4,543 30 Jul – 30 Sept · 23 days played
5,3119,999peak 9,99930 Jul30 Sept
9,999Peak Premier in tracked matches
32Days played since 2026-07-24

Premier CS Rating

  • 4,543 below peak (9,999)
  • -619 over 30 days · declining
  • Next: Blue band at 10,000 — 4,544 to go
  • Reached: Light Blue band
  • Light Blue band first seen 2026-09-06

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

MetricLast 30Previous 30Change
Matches31——
Win rate35%——
K/D0.65——
Headshot %38%——

Measured 3 Sep 2026 → 1 Oct 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 Light Blue band among CSDB-tracked players (n=8,820), 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 playerLight Blue band medianBlue band medianvs Blue band
Headshot rate32.5%39.9%41.9%9.4% short
Shot accuracy5.7%7.0%9.6%3.9% short
Kill/death ratio0.780.920.980.20 short
Match win rate36.6%42.3%43.8%7.2% short

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

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

Share this profile

CSDB.GGKressinatorPREMIER5,456 · Light Blue bandcsdb.gg/stats

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Performance scores

Aim36
Positioning41
Utility14

0–100 skill scores via Leetify.

Recent form

COLD35–57–8Last 10035%Win rateTWLLTWWLLL

Last 10 vs previous 10: −20pp win rate · −0.06 avg rating · +0.1pp headshot accuracy · +124ms reaction

Win rate down 20pp 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

  • 1–2–2 · 20% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 12%
  • Avg reaction 650ms

Last 10

  • 3–5–2 · 30% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 14%
  • Avg reaction 701ms

Last 20

  • 8–10–2 · 40% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 14%
  • Avg reaction 639ms

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 (+2.2 against its own average).

Aim3.6
Utility1.4
Positioning4.1
Opening Duels0.3

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

iM

Plays most like iM 81% playstyle similarity

Most alike: positioning profile, utility contribution.

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. 657ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 66% 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
Positioning4.1
Utility1.4
Mechanics3.7
Opening Duels1.8
Win Impact2.6

Composite 2.8/10 (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+0.06
first ⅓ avg -0.07 → last ⅓ avg -0.01
Reaction time640ms−186ms
first ⅓ avg 826ms → last ⅓ avg 640ms
Headshot accuracy14.5%+4.3%
first ⅓ avg 10.3% → last ⅓ avg 14.5%

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

0.15Best match rating · 13–4 · anubis, 19 Sept →
30%Best headshot accuracy · 13–7 · anubis, 26 Aug →
453msFastest reaction time · 9–13 · ancient, 19 Sept →
13–2Biggest win · ancient, 14 Aug →

Across the last 100 tracked matches.

Highlights

3Longest win streak
9–3In matches decided by ≤2 rounds
7Overtime games

Map breakdown

anubisBest map · 53% over 15ancientWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
infernoD196–1332%-0.06
dust2C197–1237%-0.05
anubisB158–753%-0.04
cacheC125–742%-0.03
nukeD113–827%-0.06
ancientD51–420%-0.03
mirageD51–420%-0.09
office—41–325%-0.08
train—31–233%-0.03
italy—21–150%-0.06
vertigo—21–150%-0.05
shelter—10–10%-0.05
poseidon—10–10%-0.22
debris—10–10%-0.14

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

43,362Lifetime kills
0.78K/D
3,367Matches
36.6%Match win rate
32.5%Headshot %
5.7%Shot accuracy
3,517MVPs
963Hours (in match)
3,203Bombs planted
434Bombs defused

Most-used weapons

AUG5,505
AK-474,869
SCAR-204,484
G3SG13,521
SG 5533,062
MP92,219
MAC-101,888

Lifetime map wins

4,289dust2
2,809nuke
2,649inferno
831vertigo
774train
444office
165italy
63cbble

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.

15.2%Headshot accuracy
30.5%Accuracy (enemy spotted)
32.9%Spray accuracy
66.5%Counter-strafing
11.0°Preaim
657msReaction time
38.3%T opening success
36.1%CT opening success
0.12Enemies flashed / flash
0.0%Flash assists
10.00HE damage / grenade
1.88Flashes / 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

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.1212 — below the 0.5 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 38.282% — below the 40% mark we flag

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.

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno12–12-0.0617%30 Sept →
nuke13–60.0215%30 Sept →
inferno0–2-0.090%30 Sept →
dust24–13-0.1022%30 Sept →
inferno15–15-0.057%30 Sept →
dust213–8-0.1013%29 Sept →
anubis13–30.1218%28 Sept →
cache8–130.0921%27 Sept →
nuke8–13-0.1014%27 Sept →
inferno6–13-0.0214%26 Sept →
train4–130.0010%26 Sept →
dust213–100.0617%26 Sept →
nuke13–5-0.0210%26 Sept →
dust213–9-0.058%26 Sept →
anubis10–13-0.0519%20 Sept →
anubis13–40.158%19 Sept →
dust213–160.048%19 Sept →
ancient9–130.0214%19 Sept →
inferno8–130.0721%19 Sept →
inferno13–100.0724%19 Sept →
cache13–100.1317%19 Sept →
inferno13–100.0419%19 Sept →
mirage2–13-0.0522%18 Sept →
cache1–13-0.0925%18 Sept →
cache13–11-0.0912%18 Sept →
inferno9–13-0.1026%5 Sept →
ancient12–16-0.066%5 Sept →
office6–13-0.0611%5 Sept →
italy7–13-0.0319%4 Sept →
office13–11-0.0718%4 Sept →
vertigo7–13-0.088%3 Sept →
nuke12–120.0513%3 Sept →
dust213–4-0.035%3 Sept →
inferno4–9-0.1117%3 Sept →
cache12–12-0.095%2 Sept →
train10–13-0.0512%2 Sept →
dust213–110.0215%2 Sept →
shelter8–13-0.0511%1 Sept →
dust24–13-0.098%1 Sept →
cache13–6-0.0111%31 Aug →
dust26–13-0.0311%31 Aug →
nuke7–13-0.0815%30 Aug →
cache10–13-0.0517%30 Aug →
anubis11–13-0.0813%30 Aug →
nuke10–13-0.084%26 Aug →
anubis13–7-0.0430%26 Aug →
vertigo13–9-0.0113%25 Aug →
office3–13-0.1027%25 Aug →
nuke4–9-0.176%25 Aug →
dust28–13-0.0717%25 Aug →
inferno5–13-0.0813%25 Aug →
dust210–13-0.0311%25 Aug →
anubis4–13-0.0918%24 Aug →
cache13–10-0.0710%23 Aug →
ancient9–13-0.098%23 Aug →
anubis5–13-0.077%23 Aug →
inferno13–10-0.1218%23 Aug →
dust26–13-0.0714%19 Aug →
anubis13–3-0.0917%19 Aug →
cache5–13-0.048%17 Aug →
anubis6–13-0.0914%17 Aug →
poseidon1–9-0.2212%17 Aug →
debris7–9-0.1429%17 Aug →
ancient13–20.0114%14 Aug →
dust213–16-0.124%14 Aug →
inferno7–13-0.098%14 Aug →
mirage10–13-0.1217%14 Aug →
dust27–13-0.067%14 Aug →
office12–12-0.0813%11 Aug →
dust213–11-0.023%11 Aug →
inferno2–9-0.200%11 Aug →
dust27–13-0.0616%11 Aug →
inferno7–13-0.0713%11 Aug →
dust21–13-0.0919%11 Aug →
anubis13–9-0.055%7 Aug →
mirage13–10-0.106%7 Aug →
anubis13–40.0122%7 Aug →
dust26–13-0.1112%7 Aug →
cache5–13-0.0910%7 Aug →
inferno13–11-0.0712%5 Aug →
inferno8–13-0.0813%2 Aug →
nuke10–13-0.115%2 Aug →
anubis8–13-0.069%2 Aug →
nuke15–15-0.0618%31 Jul →
ancient15–15-0.056%31 Jul →
dust213–7-0.0610%30 Jul →
nuke16–14-0.058%30 Jul →
inferno10–13-0.1010%30 Jul →
inferno13–11-0.0610%30 Jul →
cache13–8-0.047%29 Jul →
inferno13–11-0.0120%29 Jul →
cache5–13-0.0512%29 Jul →
anubis13–6-0.070%29 Jul →
mirage3–13-0.146%29 Jul →
italy13–8-0.080%28 Jul →
anubis13–2-0.0613%28 Jul →
train13–11-0.0519%28 Jul →
nuke12–12-0.058%27 Jul →
mirage6–13-0.0518%27 Jul →
anubis7–13-0.0812%24 Jul →

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 →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.