figo

figo — CS2 Stats

MR76561198333741045[U:1:373475317]Steam profile ↗✓ No bans

409Tracked matches38%Win rate2020Tracked since
1,907Hours in CS19Hrs last 2 wks
CSDB Rating5.9 SolidPositional Player
Premier CS Rating17,633Purple band · top ~17.9% of ranked players (population est.)
FaceitLevel 9Top 20.7% of ranked FACEIT players
WingmanLegendary Eagle Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 24 Oct 2026 (21 days ago). Ranks are recorded once per day this page is viewed.

0Premier CS Rating · 17,633 → 17,633
+13Tracked matches · now 409
−3.4ppWin rate · 41.4% → 37.9%

Rating over time

Premier CS Rating: 17,633 +7,215 16 Dec – 24 Oct · 16 days played
10,41817,633peak 17,63316 Dec24 Oct
17,633Peak Premier in tracked matches
73Days played since 2024-12-16

Premier CS Rating

  • At peak — 17,633
  • +1,211 over 30 days · improving
  • Next: Pink band at 20,000 — 2,367 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-10-24
  • Blue band first seen 2026-10-24

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

How this compares with the same rank

Median values for Level 9 among CSDB-tracked players (n=15,132), 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 9 medianLevel 10 medianvs Level 10
Headshot rate49.8%48.2%50.9%1.1% short
Shot accuracy10.5%13.2%13.7%3.2% short
Kill/death ratio0.931.071.090.15 short
Match win rate44.3%46.9%48.4%4.1% short

This profile sits below the typical Level 10 player on every metric we can compare.

Widest gap: Shot accuracy. That is the metric furthest from the Level 10 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGfigoFACEITLevel 9STANDINGTop 20.7% of rankedPREMIER17,633 · Purple bandcsdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim81
Positioning58
Utility47

0–100 skill scores via Leetify.

Recent form

STEADY55–40–5Last 10055%Win rateLWLLWWLLWL

Last 10 vs previous 10: −20pp win rate · −0.01 avg rating · +0.9pp headshot accuracy · −32ms 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

  • 2–3 · 40% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 21%
  • Avg reaction 561ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 22%
  • Avg reaction 531ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 22%
  • 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: Positional Player — Positioning stands above the rest of this profile (+1.3 against its own average).

Aim8.1
Utility4.7
Positioning5.8
Opening Duels4.0
Clutch3.6

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

Twistzz

Plays most like Twistzz 89% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: lower aim profile; lower utility contribution.

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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 562ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

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

Aim8.1
Positioning5.8
Utility4.7
Mechanics7.1
Opening Duels4.0
Win Impact1.0

Composite 5.9/10 (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 rating0.03+0.01
first ⅓ avg 0.03 → last ⅓ avg 0.03
Reaction time578ms−6ms
first ⅓ avg 584ms → last ⅓ avg 578ms
Headshot accuracy21.8%+1.3%
first ⅓ avg 20.5% → last ⅓ avg 21.8%

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

0.28Best match rating · 9–2 · inferno, 5 Oct →
47%Best headshot accuracy · 13–2 · mirage, 26 Oct →
398msFastest reaction time · 9–5 · inferno, 30 Sept →
13–2Biggest win · mirage, 26 Oct →

Across the last 100 tracked matches.

Highlights

6Longest win streak
11–4In matches decided by ≤2 rounds
16Overtime games

Map breakdown

overpassBest map · 67% over 6anubisWeakest map · 38% over 8
MapGradePlayedRecordWin rateAvg rating
infernoA1911–858%0.03
dust2S1711–665%0.04
mirageA127–558%0.01
ancientC125–742%0.02
nukeA116–555%0.03
anubisC83–538%0.03
trainA74–357%-0.01
overpassS64–267%0.02
cache—40–40%0.01
vertigo—33–0100%0.14
brewery—11–0100%-0.02

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (38% over 8). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

57,606Lifetime kills
0.93K/D
3,123Matches
44.3%Match win rate
49.8%Headshot % · Top 50% of Level 9 players
10.5%Shot accuracy
8,890MVPs
1,088Hours (in match)
3,442Bombs planted
999Bombs defused

Most-used weapons

AK-4718,361
AWP3,941
MP71,198
SG 5531,181
MP91,122

Lifetime map wins

3,564inferno
3,104dust2
1,864nuke
1,833train
1,272vertigo
1,188cbble
182lake
90office

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

Faceit stats

Combat

726Matches
51%Win rate
1.09Avg K/D
88.2ADR
50%Headshot %

Clutches & streaks

38%1v1 clutch win
24%1v2 clutch win
7Longest win streak

Recent Faceit resultsWLWLW

MapMatchesWin rateAvg K/DAvg kills
Mirage19355%1.1117.2
Ancient7748%1.1617.9
Dust27445%1.0617.1
Anubis5655%1.4019.6
Train4058%1.0517.9
Inferno3639%1.0417.2
Nuke2642%1.2520.1
Cache2446%1.3519.8

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.

20.6%Headshot accuracy
35.1%Accuracy (enemy spotted)
39.7%Spray accuracy
82.1%Counter-strafing
8.6°Preaim
562msReaction time
47.3%T opening success
45.0%CT opening success
0.56Enemies flashed / flash
5.7%Flash assists
6.36HE damage / grenade
6.74Flashes / match

Recommended for you

Spend your practice time on Anubis

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

38% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis16–190.0518%13 Nov →
mirage13–110.0528%12 Nov →
ancient5–13-0.0722%5 Nov →
cache2–13-0.0325%4 Nov →
inferno13–110.0214%12 Oct →
inferno9–20.2831%5 Oct →
ancient23–25-0.0411%5 Oct →
cache6–130.0832%24 Sept →
anubis13–100.0217%17 Sept →
cache2–13-0.0927%16 Sept →
ancient13–80.1722%14 Sept →
nuke9–60.0416%11 Sept →
dust213–110.0529%7 Sept →
inferno13–80.0322%2 Sept →
ancient5–13-0.0320%29 Aug →
dust210–13-0.0518%28 Aug →
dust213–40.0816%23 Aug →
nuke10–13-0.0128%22 Aug →
dust213–50.1121%22 Aug →
dust22–13-0.0224%4 Jul →
nuke13–50.1035%1 Jul →
cache7–130.0819%12 Jun →
ancient11–13-0.0215%11 Jun →
inferno13–11-0.0715%5 Jun →
overpass8–130.1224%4 Jun →
inferno13–160.0313%4 Jun →
dust26–130.0319%25 Apr →
anubis7–130.0320%5 Feb →
ancient13–7-0.0314%5 Feb →
inferno6–130.0626%2 Feb →
dust23–130.0632%28 Jan →
inferno9–40.0727%22 Jan →
inferno15–15-0.0519%15 Jan →
dust28–130.0733%13 Jan →
nuke10–130.0311%1 Jan →
nuke9–2-0.0015%27 Oct →
inferno6–90.0111%27 Oct →
mirage13–70.0026%27 Oct →
mirage13–20.1647%26 Oct →
inferno19–170.0042%22 Oct →
train13–10-0.0022%19 Oct →
overpass13–10-0.0422%18 Oct →
inferno10–13-0.0720%17 Oct →
mirage7–13-0.0622%17 Oct →
dust213–100.0328%15 Oct →
ancient19–170.0124%14 Oct →
nuke16–13-0.0517%13 Oct →
vertigo9–50.0220%12 Oct →
dust213–60.0525%8 Oct →
train13–160.0414%8 Oct →
dust213–70.0712%5 Oct →
train15–15-0.0025%5 Oct →
train13–11-0.0113%2 Oct →
vertigo9–30.1821%30 Sept →
vertigo9–10.2316%30 Sept →
inferno9–50.0322%30 Sept →
inferno9–50.0715%30 Sept →
mirage10–130.0629%30 Sept →
train13–9-0.0513%30 Sept →
brewery9–7-0.0220%30 Sept →
dust213–50.0330%30 Sept →
overpass13–50.0530%30 Sept →
train9–13-0.0422%27 Sept →
mirage13–8-0.0223%24 Sept →
overpass16–130.0317%24 Sept →
mirage14–16-0.0215%24 Sept →
mirage13–10-0.0128%21 Sept →
inferno14–16-0.047%20 Sept →
ancient10–130.018%20 Sept →
mirage13–30.0221%19 Sept →
ancient13–110.0021%14 Sept →
dust216–13-0.0124%14 Sept →
dust213–70.0432%9 Sept →
ancient13–80.0319%6 Sept →
train13–90.0224%1 Sept →
overpass10–13-0.029%1 Sept →
overpass13–80.008%24 Aug →
anubis13–90.0334%24 Aug →
inferno8–80.0718%8 Aug →
nuke5–130.0923%7 Aug →
anubis10–13-0.0113%12 Jul →
nuke13–50.1127%13 Jun →
nuke13–70.0410%13 Jun →
anubis10–130.0232%12 Jun →
ancient4–130.0533%6 Jun →
nuke8–13-0.0126%6 Jun →
dust213–100.0111%31 May →
inferno15–15-0.0220%28 May →
inferno13–50.1319%28 May →
anubis13–60.1021%10 May →
anubis7–130.0121%10 May →
mirage13–110.0111%9 May →
inferno13–11-0.0115%19 Apr →
nuke1–13-0.0212%16 Apr →
dust213–160.0531%10 Apr →
inferno9–40.0541%8 Apr →
ancient15–150.0917%5 Apr →
dust213–90.0322%2 Apr →
mirage10–130.0530%6 Mar →
mirage0–6-0.0617%16 Dec →

Match data via Leetify.

Recent teammates

Milestones

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

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