A Fat HotPocket

A Fat HotPocket — CS2 Stats

76561199122221822[U:1:1161956094]Steam profile ↗✓ No bans

1,339Tracked matches59%Win rate2025Tracked since
1,500Hours in CS77Hrs last 2 wks
CSDB Rating4.1 DevelopingPositional Player
Premier CS Rating6,111Light Blue band · top ~73.5% of ranked players (population est.)
FaceitLevel 3Top 90.6% of ranked FACEIT players
WingmanSilver Elite
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 18 Oct 2026 (yesterday). Ranks are recorded once per day this page is viewed.

+507Premier CS Rating · 5,604 → 6,111

Rating over time

Premier CS Rating: 6,111 +2,622 18 Sept – 19 Oct · 17 days played
3,4896,111peak 6,11118 Sept19 Oct
6,111Peak Premier in tracked matches
19Days played since 2026-09-18

Premier CS Rating

  • At peak — 6,111
  • +2,622 over 30 days · improving
  • Next: Blue band at 10,000 — 3,889 to go
  • Reached: Light Blue band

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
Matches214——
Win rate50%——
K/D0.97——
Headshot %29%——

Measured 18 Sep 2026 → 19 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 Level 3 among CSDB-tracked players (n=10,259), 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 3 medianLevel 4 medianvs Level 4
Headshot rate31.4%41.8%42.7%11.4% short
Shot accuracy0.2%12.2%11.3%11.1% short
Kill/death ratio0.750.980.990.25 short
Match win rate41.7%43.3%43.9%2.2% short

This profile sits below the typical Level 4 player on every metric we can compare.

Widest gap: Shot accuracy. That is the metric furthest from the Level 4 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGA Fat HotPocketFACEITLevel 3STANDINGTop 90.6% of rankedPREMIER6,111 · Light Blue bandcsdb.gg/stats

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Performance scores

Aim35
Positioning52
Utility38

0–100 skill scores via Leetify.

Recent form

STEADY52–44–4Last 10052%Win rateWWLLWTWWWL

Last 10 vs previous 10: 0pp win rate · −0.05 avg rating · −6.3pp headshot accuracy · +49ms 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

  • 3–2 · 60% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 11%
  • Avg reaction 725ms

Last 10

  • 6–3–1 · 60% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 10%
  • Avg reaction 662ms

Last 20

  • 12–6–2 · 60% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 13%
  • 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: Positional Player — Positioning stands above the rest of this profile (+1.5 against its own average).

Aim3.5
Utility3.8
Positioning5.2
Opening Duels3.3
Clutch2.6

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 70% 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. 617ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 68% 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

Aim3.5
Positioning5.2
Utility3.8
Mechanics3.9
Opening Duels5.0
Win Impact7.9

Composite 4.1/10 (Developing), 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 rating0.01+0.02
first ⅓ avg -0.01 → last ⅓ avg 0.01
Reaction time622ms−5ms
first ⅓ avg 627ms → last ⅓ avg 622ms
Headshot accuracy11.5%+0.4%
first ⅓ avg 11.2% → last ⅓ avg 11.5%

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 · 13–10 · inferno, 26 Sept →
50%Best headshot accuracy · 13–2 · inferno, 18 Oct →
422msFastest reaction time · 12–12 · anubis, 1 Oct →
13–1Biggest win · cache, 18 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak
W2Current streak
7–8In matches decided by ≤2 rounds
6Overtime games

Map breakdown

cacheBest map · 71% over 7ancientWeakest map · 33% over 9
MapGradePlayedRecordWin rateAvg rating
mirageS2315–865%0.00
anubisC167–944%-0.01
dust2B137–654%-0.02
infernoA116–555%-0.01
nukeB105–550%0.01
ancientD93–633%0.02
cacheS75–271%-0.00
train—41–325%-0.02
debris—31–233%0.09
office—31–233%0.02
vertigo—11–0100%-0.07

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

24,130Lifetime kills
0.75K/D
2,114Matches
41.7%Match win rate
31.4%Headshot %
0.2%Shot accuracy
3,340MVPs
717Hours (in match)
1,933Bombs planted
394Bombs defused

Most-used weapons

Lifetime map wins

3,805dust2
3,115nuke
2,499inferno
1,031vertigo
545office
208train
8assault
8cbble

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

Faceit stats

Combat

243Matches
47%Win rate
0.86Avg K/D
69.9ADR
33%Headshot %

Clutches & streaks

33%1v1 clutch win
23%1v2 clutch win
6Longest win streak

Recent Faceit resultsWLLLL

MapMatchesWin rateAvg K/DAvg kills
Mirage7844%0.8412.7
Dust24842%0.8213.4
Nuke3656%0.9013.8
Anubis2948%0.9815.2
Cache1753%0.8214.3
Inferno1656%0.9012.3
Ancient933%0.8312.9
Vertigo944%0.7314.2

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.

11.1%Headshot accuracy
29.6%Accuracy (enemy spotted)
31.1%Spray accuracy
67.6%Counter-strafing
10.0°Preaim
617msReaction time
51.2%T opening success
48.5%CT opening success
0.50Enemies flashed / flash
1.0%Flash assists
9.66HE damage / grenade
5.09Flashes / 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 11.1365% — 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.

33% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache13–6-0.0320%19 Oct →
mirage16–120.0019%19 Oct →
ancient7–13-0.035%19 Oct →
mirage7–13-0.023%18 Oct →
mirage13–8-0.036%18 Oct →
mirage15–15-0.0213%18 Oct →
ancient13–50.067%18 Oct →
cache13–4-0.019%18 Oct →
nuke13–9-0.0110%18 Oct →
cache5–13-0.014%18 Oct →
mirage13–70.0413%18 Oct →
dust213–60.1224%18 Oct →
nuke12–20.0110%18 Oct →
inferno13–20.0750%18 Oct →
debris8–80.1210%18 Oct →
mirage13–60.049%18 Oct →
cache13–10.006%18 Oct →
ancient11–130.059%18 Oct →
anubis2–130.0229%18 Oct →
inferno5–13-0.040%17 Oct →
mirage13–11-0.007%17 Oct →
mirage13–10.078%17 Oct →
anubis16–140.0214%17 Oct →
nuke8–13-0.030%17 Oct →
nuke16–120.0514%17 Oct →
dust22–8-0.0517%17 Oct →
debris9–70.1313%17 Oct →
mirage9–13-0.0112%16 Oct →
vertigo13–10-0.074%16 Oct →
dust26–13-0.035%16 Oct →
mirage6–13-0.057%15 Oct →
anubis8–13-0.0212%15 Oct →
anubis2–13-0.0715%15 Oct →
anubis16–12-0.015%15 Oct →
dust25–13-0.0620%15 Oct →
anubis9–13-0.109%15 Oct →
inferno13–10-0.0816%14 Oct →
mirage7–13-0.0518%14 Oct →
mirage10–13-0.020%13 Oct →
nuke13–80.1217%12 Oct →
ancient13–80.0414%11 Oct →
ancient13–30.0413%11 Oct →
office11–130.0511%11 Oct →
nuke13–30.0315%11 Oct →
inferno12–2-0.003%11 Oct →
dust213–110.0215%11 Oct →
inferno13–10-0.047%11 Oct →
mirage13–4-0.022%11 Oct →
cache7–130.0110%10 Oct →
anubis13–70.028%10 Oct →
nuke10–130.0417%10 Oct →
anubis13–5-0.067%10 Oct →
inferno4–13-0.0117%9 Oct →
debris7–90.012%9 Oct →
mirage13–90.046%9 Oct →
office13–70.0512%9 Oct →
train4–13-0.0311%9 Oct →
train3–13-0.077%9 Oct →
nuke6–13-0.0311%8 Oct →
mirage13–6-0.0218%8 Oct →
cache13–60.0416%8 Oct →
mirage9–13-0.0311%8 Oct →
mirage13–100.047%1 Oct →
office8–13-0.0510%1 Oct →
anubis12–120.116%1 Oct →
cache13–3-0.0421%1 Oct →
mirage13–80.0618%1 Oct →
dust211–13-0.1012%1 Oct →
anubis5–12-0.0018%30 Sept →
inferno2–13-0.0618%30 Sept →
train13–60.0111%30 Sept →
inferno6–13-0.0124%30 Sept →
ancient3–130.049%30 Sept →
inferno6–13-0.0611%30 Sept →
mirage11–13-0.016%29 Sept →
ancient7–13-0.0813%29 Sept →
anubis13–90.022%29 Sept →
mirage13–5-0.017%29 Sept →
anubis11–13-0.060%29 Sept →
mirage13–70.0214%27 Sept →
anubis13–11-0.0310%27 Sept →
ancient10–13-0.016%27 Sept →
dust213–110.0212%27 Sept →
mirage13–3-0.0216%27 Sept →
nuke11–130.0217%26 Sept →
inferno13–100.1515%26 Sept →
ancient5–130.0410%25 Sept →
mirage13–70.0212%25 Sept →
dust214–160.0213%25 Sept →
dust213–9-0.0012%25 Sept →
dust213–9-0.133%25 Sept →
anubis13–6-0.0313%25 Sept →
inferno13–6-0.0411%25 Sept →
anubis8–130.057%24 Sept →
dust21–10-0.098%24 Sept →
dust213–110.0420%24 Sept →
dust213–40.0411%24 Sept →
train12–12-0.0116%24 Sept →
nuke7–3-0.045%24 Sept →
anubis9–13-0.038%24 Sept →

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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