Fatsch

Fatsch — CS2 Stats

DE76561198024112734[U:1:63847006]Steam profile ↗✓ No bans

976Tracked matches41%Win rate2020Tracked since
CSDB Rating3.1 LearningSupport
Premier CS Rating6,311Light Blue band · top ~72.5% of ranked players (population est.)
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 7 Sep 2026 (13 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.

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. 45 days played since 19 Apr 2026. Come back after the next session and the change shows above.

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Rating over time

Premier CS Rating: 6,311 +2,725 8 Jun20 Sept · 18 days played
3,1506,311peak 6,3118 Jun20 Sept
6,311Peak Premier in tracked matches
45Days played since 2026-04-19

Premier CS Rating

  • At peak — 6,311
  • +2,602 over 90 days
  • Next: Blue band at 10,000 3,689 to go
  • Reached: Light Blue band
  • Light Blue band first seen 2026-09-20

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

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CSDB.GGFatschPREMIER6,311 · Light Blue bandcsdb.gg/stats

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Performance scores

Aim32
Positioning45
Utility48

0–100 skill scores via Leetify.

Recent form

STEADY40555Last 10040%Win rateWLWWLWLLLL

Last 10 vs previous 10: 0pp win rate · +0.01 avg rating · +0.1pp headshot accuracy · −10ms reaction

Win rate 0pp 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

  • 32 · 60% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 10%
  • Avg reaction 706ms

Last 10

  • 46 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 10%
  • Avg reaction 630ms

Last 20

  • 812 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 10%
  • Avg reaction 635ms

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 (+0.9 against its own average).

Aim3.2
Utility4.8
Positioning4.5
Opening Duels2.5

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

jL

Plays most like jL 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 25% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 639ms 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

Aim3.2
Positioning4.5
Utility4.8
Mechanics3.4
Opening Duels1.6
Win Impact2.1

Composite 3.1/10 (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-0.02−0.02
first ⅓ avg -0.01 → last ⅓ avg -0.02
Reaction time639ms−35ms
first ⅓ avg 674ms → last ⅓ avg 639ms
Headshot accuracy10.1%−1.7%
first ⅓ avg 11.8% → last ⅓ avg 10.1%

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

0.13Best match rating · 9–3 · overpass, 30 Jun
28%Best headshot accuracy · 13–5 · cache, 30 May
422msFastest reaction time · 7–9 · vertigo, 20 Jun
13–3Biggest win · inferno, 3 Jul

Across the last 100 tracked matches.

Highlights

4Longest win streak
78In matches decided by ≤2 rounds
7Overtime games

Map breakdown

infernoBest map · 50% over 10nukeWeakest map · 30% over 20
MapGradePlayedRecordWin rateAvg rating
nukeD2061430%-0.02
ancientC2081240%-0.02
anubisC145936%-0.02
cacheC135838%-0.02
infernoB105550%-0.02
overpassB84450%-0.00
mirageC52340%-0.01
dust2C52340%-0.03
vertigo2020%-0.02
debris110100%-0.03
poseidon110100%-0.06
train110100%0.02

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (30% over 20). Start with the 6 essential Nuke 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.

10.1%Headshot accuracy
32.0%Accuracy (enemy spotted)
36.5%Spray accuracy
65.4%Counter-strafing
11.8°Preaim
639msReaction time
25.0%T opening success
42.7%CT opening success
0.62Enemies flashed / flash
4.4%Flash assists
12.63HE damage / grenade
3.29Flashes / 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 10.0672% — below the 15% mark we flag

    Aim Training
  2. Grenades & Utility

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

    Flashes per match 3.2898 — below the 4 mark we flag

    Grenade Lineups
  3. 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 24.9765% — below the 40% mark we flag

Spend your practice time on Nuke

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

30% win rate across 20 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategyNuke grenade lineups

Recent matches

MapScoreRatingHS%Date
nuke13–100.018%7 Sept
cache10–130.0713%2 Sept
mirage16–14-0.0111%2 Sept
cache13–9-0.056%31 Aug
cache9–13-0.0114%31 Aug
ancient13–5-0.055%31 Aug
ancient8–13-0.0313%30 Aug
dust25–13-0.077%30 Aug
nuke9–13-0.016%30 Aug
ancient7–13-0.0514%28 Aug
nuke5–13-0.0913%28 Aug
inferno13–4-0.0216%23 Aug
anubis11–13-0.067%23 Aug
mirage13–8-0.0410%23 Aug
cache13–6-0.0312%21 Aug
nuke5–13-0.064%21 Aug
ancient8–130.039%21 Aug
nuke13–11-0.027%21 Aug
nuke11–130.009%17 Aug
ancient6–13-0.069%17 Aug
anubis13–10-0.055%15 Aug
anubis13–80.0214%15 Aug
inferno9–130.018%2 Aug
nuke13–110.0114%2 Aug
inferno8–13-0.0114%27 Jul
cache10–13-0.0722%19 Jul
ancient1–13-0.010%19 Jul
ancient4–13-0.034%19 Jul
ancient13–40.039%18 Jul
nuke15–15-0.0512%17 Jul
anubis2–13-0.0515%11 Jul
ancient13–11-0.049%11 Jul
vertigo8–80.0413%11 Jul
debris9–5-0.0317%10 Jul
ancient7–13-0.0513%6 Jul
nuke11–13-0.0612%5 Jul
inferno13–11-0.035%5 Jul
ancient2–13-0.017%5 Jul
overpass13–8-0.0011%5 Jul
cache9–13-0.0323%5 Jul
anubis15–15-0.0511%4 Jul
ancient8–13-0.087%3 Jul
nuke5–13-0.0910%3 Jul
ancient13–7-0.0710%3 Jul
nuke4–13-0.078%3 Jul
inferno13–30.0914%3 Jul
anubis3–13-0.0019%1 Jul
anubis13–7-0.027%1 Jul
anubis9–13-0.079%30 Jun
inferno13–110.0120%30 Jun
overpass9–30.137%30 Jun
nuke9–40.098%30 Jun
ancient13–50.0011%27 Jun
anubis9–130.0916%27 Jun
poseidon9–7-0.0618%27 Jun
overpass13–160.0412%24 Jun
dust213–6-0.0313%24 Jun
dust26–13-0.065%22 Jun
ancient13–40.037%22 Jun
overpass13–5-0.0316%21 Jun
nuke10–13-0.1014%21 Jun
vertigo7–9-0.0815%20 Jun
overpass13–7-0.067%20 Jun
dust28–13-0.0113%17 Jun
anubis5–13-0.068%17 Jun
anubis8–13-0.029%15 Jun
overpass9–13-0.0511%9 Jun
ancient13–9-0.0014%8 Jun
nuke10–130.065%2 Jun
inferno7–13-0.077%30 May
cache13–5-0.0328%30 May
inferno7–13-0.0814%30 May
train13–70.0212%30 May
cache0–13-0.0515%30 May
nuke11–130.0111%28 May
mirage4–13-0.030%28 May
overpass9–130.0012%23 May
mirage9–13-0.0011%23 May
overpass11–13-0.0412%22 May
nuke13–40.029%22 May
anubis13–60.0711%20 May
ancient10–130.0220%20 May
ancient13–6-0.004%19 May
dust216–130.0418%17 May
cache13–60.099%16 May
mirage9–130.0315%16 May
inferno11–13-0.0616%16 May
anubis13–5-0.0610%16 May
nuke7–13-0.040%16 May
anubis7–13-0.0421%13 May
inferno13–60.005%13 May
nuke10–130.0121%13 May
nuke15–150.0213%8 May
ancient15–15-0.029%2 May
nuke13–8-0.039%2 May
cache13–10-0.0520%1 May
cache9–130.038%1 May
cache11–13-0.056%1 May
cache10–13-0.049%1 May
ancient10–130.0718%19 Apr

Match data via Leetify.

Recent teammates

Milestones

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