Fat tony

Fat tony — CS2 Stats

FI76561198869406926[U:1:909141198]Steam profile ↗✓ No bans

530Tracked matches48%Win rate2020Tracked since
CSDB Rating6.3 SolidSupport
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 20 Sep 2026 (46 days ago). Ranks are recorded once per day this page is viewed.

+15Tracked matches · now 530
+13.4ppWin rate · 34.6% → 48.0%

Rating over time

39Days played since 2026-04-10

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled.

Performance scores

Aim76
Positioning48
Utility72

0–100 skill scores via Leetify.

Recent form

COLD49–40–11Last 10049%Win rateWWTLLTLLLW

Last 10 vs previous 10: −40pp win rate · −0.04 avg rating · −2.7pp headshot accuracy · +16ms reaction

Win rate down 40pp 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

  • 2–2–1 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 19%
  • Avg reaction 625ms

Last 10

  • 3–5–2 · 30% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 17%
  • Avg reaction 570ms

Last 20

  • 10–7–3 · 50% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 18%
  • Avg reaction 561ms

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 (+2.2 against its own average).

Aim7.6
Utility7.2
Positioning4.8
Opening Duels3.0

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

ZywOo

Plays most like ZywOo 87% 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 55% on CT to 38% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim7.6
Positioning4.8
Utility7.2
Mechanics7.7
Opening Duels4.2
Win Impact4.3

Composite 6.3/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02−0.01
first ⅓ avg 0.02 → last ⅓ avg 0.02
Reaction time551ms−52ms
first ⅓ avg 603ms → last ⅓ avg 551ms
Headshot accuracy19.3%−5.7%
first ⅓ avg 25.0% → last ⅓ avg 19.3%

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

0.16Best match rating · 10–1 · cache, 2 Aug →
70%Best headshot accuracy · 5–13 · vertigo, 3 Jun →
391msFastest reaction time · 4–13 · inferno, 8 Oct →
13–0Biggest win · dust2, 13 May →

Across the last 100 tracked matches.

Highlights

6Longest win streak
W2Current streak
1–6In matches decided by ≤2 rounds
1Overtime games

Map breakdown

nukeBest map · 60% over 5trainWeakest map · 30% over 10
MapGradePlayedRecordWin rateAvg rating
cacheB189–950%0.02
infernoA127–558%0.03
mirageB115–645%0.00
anubisB105–550%0.05
trainD103–730%-0.02
dust2A95–456%0.03
officeC83–538%0.01
vertigoA74–357%-0.00
ancientB63–350%0.02
nukeA53–260%0.02
overpass—42–250%0.02

Across the last 100 tracked matches.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

18.5%Headshot accuracy
35.9%Accuracy (enemy spotted)
40.6%Spray accuracy
84.5%Counter-strafing
11.5°Preaim
549msReaction time
38.5%T opening success
54.8%CT opening success
0.52Enemies flashed / flash
12.3%Flash assists
9.19HE damage / grenade
12.83Flashes / 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

    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 38.4677% — below the 40% mark we flag

Spend your practice time on Train

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 10 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
anubis13–50.0429%31 Oct →
overpass13–10.1517%31 Oct →
office12–120.0122%31 Oct →
anubis10–130.0013%23 Oct →
cache4–13-0.0813%23 Oct →
cache12–120.0213%22 Oct →
cache4–13-0.0616%22 Oct →
inferno4–13-0.046%8 Oct →
train11–13-0.0418%8 Oct →
train13–70.0118%7 Oct →
inferno13–100.0212%2 Oct →
dust213–100.0516%2 Oct →
dust213–50.0621%28 Sept →
vertigo13–10.0721%28 Sept →
vertigo13–30.0728%28 Sept →
anubis10–130.0622%18 Sept →
anubis13–30.0823%18 Sept →
mirage12–12-0.009%18 Sept →
nuke13–100.0113%15 Sept →
ancient3–13-0.0027%15 Sept →
anubis10–130.0120%11 Sept →
mirage6–13-0.0721%11 Sept →
office11–130.0819%3 Sept →
office13–60.0219%3 Sept →
inferno12–120.0824%1 Sept →
dust211–13-0.016%1 Sept →
overpass2–13-0.0118%27 Aug →
cache12–120.0525%27 Aug →
cache10–13-0.0128%27 Aug →
inferno13–7-0.0325%21 Aug →
mirage8–13-0.0331%21 Aug →
ancient9–10.0822%21 Aug →
dust26–13-0.0521%21 Aug →
train12–120.0433%12 Aug →
train8–13-0.0818%12 Aug →
dust21–13-0.0117%12 Aug →
train7–13-0.0916%12 Aug →
train11–13-0.0217%12 Aug →
ancient13–4-0.0319%6 Aug →
cache5–13-0.0824%3 Aug →
dust26–130.0422%2 Aug →
cache10–10.1626%2 Aug →
vertigo13–70.0214%29 Jul →
vertigo10–13-0.0232%29 Jul →
mirage13–80.0119%22 Jul →
anubis13–8-0.0219%22 Jul →
anubis10–130.0531%22 Jul →
inferno13–90.1014%20 Jul →
mirage13–70.0828%20 Jul →
inferno13–90.1319%10 Jul →
office13–90.0216%8 Jul →
office7–13-0.1028%8 Jul →
mirage10–13-0.0232%8 Jul →
office7–130.0429%8 Jul →
cache13–90.0521%1 Jul →
cache13–60.0819%1 Jul →
inferno8–130.0215%1 Jul →
inferno3–13-0.0910%24 Jun →
cache13–5-0.0216%24 Jun →
ancient3–13-0.0723%18 Jun →
overpass11–130.0122%18 Jun →
ancient13–70.1129%18 Jun →
nuke13–90.0418%18 Jun →
anubis13–70.1017%18 Jun →
train13–50.0516%17 Jun →
train7–13-0.1113%17 Jun →
cache13–80.0128%17 Jun →
mirage13–50.0123%17 Jun →
overpass13–5-0.0512%10 Jun →
nuke8–13-0.0124%10 Jun →
ancient11–130.0032%3 Jun →
vertigo13–50.0118%3 Jun →
vertigo2–13-0.0817%3 Jun →
vertigo5–13-0.0970%3 Jun →
mirage13–90.0216%28 May →
inferno7–130.1128%27 May →
train13–110.0429%27 May →
cache13–1-0.0033%27 May →
anubis13–60.1214%27 May →
anubis10–130.0720%27 May →
inferno13–90.0620%20 May →
dust213–80.1125%20 May →
office13–50.0227%13 May →
office12–12-0.0221%13 May →
inferno13–7-0.0115%13 May →
nuke1–13-0.0230%13 May →
dust213–00.0330%13 May →
cache12–120.1033%7 May →
cache5–13-0.0614%7 May →
cache8–20.0554%7 May →
mirage12–120.0829%29 Apr →
cache13–50.0326%29 Apr →
cache6–20.1020%29 Apr →
cache8–13-0.0323%29 Apr →
train12–120.0320%22 Apr →
inferno13–90.0228%20 Apr →
mirage16–12-0.0714%20 Apr →
mirage12–120.019%16 Apr →
dust213–40.0818%16 Apr →
nuke13–50.0732%10 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 →

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