Spoo^

Spoo^ — CS2 Stats

DK76561197960329226[U:1:63498]Steam profile ↗✓ No bans

444Tracked matches53%Win rate2020Tracked since
CSDB Rating4.1 DevelopingSupport
FaceitLevel 1Top 100.0% of ranked FACEIT players
WingmanSilver III
Ladder ranks via Leetify

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CSDB.GGSpoo^FACEITLevel 1STANDINGTop 100.0% of rankedcsdb.gg/stats

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Performance scores

Aim43
Positioning21
Utility51

0–100 skill scores via Leetify.

Recent form

HOT47–53Last 10047%Win rateWLWWLWWWWL

Last 10 vs previous 10: +30pp win rate · +0.01 avg rating · −3.1pp headshot accuracy · −4ms reaction

Win rate up 30pp 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

  • 3–2 · 60% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 5%
  • Avg reaction 775ms

Last 10

  • 7–3 · 70% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 8%
  • Avg reaction 694ms

Last 20

  • 11–9 · 55% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 10%
  • Avg reaction 696ms

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 (+2.7 against its own average).

Aim4.3
Utility5.1
Positioning2.1
Opening Duels0.0
Clutch2.6

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

ZywOo

Plays most like ZywOo 74% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower aim profile; lower opening-duel success.

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. 687ms 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

Aim4.3
Positioning2.1
Utility5.1
Mechanics6.5
Opening Duels0.0
Win Impact6.1

Composite 4.1/10 (Developing), 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 rating-0.07−0.02
first ⅓ avg -0.05 → last ⅓ avg -0.07
Reaction time696ms−56ms
first ⅓ avg 752ms → last ⅓ avg 696ms
Headshot accuracy11.7%−0.7%
first ⅓ avg 12.4% → last ⅓ avg 11.7%

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

0.04Best match rating · 9–4 · vertigo, 19 Apr →
50%Best headshot accuracy · 13–4 · anubis, 12 Jun →
516msFastest reaction time · 6–13 · nuke, 28 Aug →
13–1Biggest win · nuke, 13 Nov →

Across the last 100 tracked matches.

Highlights

6Longest win streak
13–5In matches decided by ≤2 rounds
8Overtime games

Map breakdown

vertigoBest map · 60% over 5infernoWeakest map · 36% over 28
MapGradePlayedRecordWin rateAvg rating
infernoC2810–1836%-0.07
nukeB2312–1152%-0.06
ancientA1710–759%-0.07
anubisC94–544%-0.06
overpassC94–544%-0.05
vertigoA53–260%-0.02
mirage—42–250%-0.07
dust2—20–20%-0.08
train—21–150%-0.07
cache—11–0100%-0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (36% over 28). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

187Matches
44%Win rate
0.54Avg K/D
47.1ADR
36%Headshot %

Clutches & streaks

33%1v1 clutch win
7%1v2 clutch win
4Longest win streak

Recent Faceit resultsWWWWL

MapMatchesWin rateAvg K/DAvg kills
Ancient956%0.508.1
Nuke956%0.508.3
Inferno838%0.427.6
Anubis60%0.5411.2
Dust2333%0.477.7
Overpass2100%0.9010.5
Mirage10%0.274.0

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.

11.2%Headshot accuracy
32.1%Accuracy (enemy spotted)
31.5%Spray accuracy
79.2%Counter-strafing
9.7°Preaim
687msReaction time
16.1%T opening success
21.2%CT opening success
0.50Enemies flashed / flash
3.3%Flash assists
7.55HE damage / grenade
4.76Flashes / 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 11.231% — below the 15% mark we flag

    Aim Training →
  2. 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 0.497 — below the 0.5 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 16.085% — below the 40% mark we flag

Spend your practice time on Inferno

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

36% win rate across 28 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke13–2-0.024%22 Oct →
inferno7–13-0.067%22 Oct →
cache13–11-0.045%22 Oct →
inferno13–7-0.070%15 Oct →
dust26–13-0.109%15 Oct →
nuke13–9-0.0421%15 Oct →
nuke16–14-0.083%24 Sept →
ancient13–8-0.109%24 Sept →
inferno13–11-0.1020%17 Sept →
nuke12–16-0.094%17 Sept →
mirage11–5-0.100%10 Sept →
nuke9–13-0.0611%10 Sept →
anubis13–11-0.0410%10 Sept →
anubis13–9-0.089%3 Sept →
ancient4–13-0.106%3 Sept →
inferno12–16-0.1021%20 Aug →
nuke10–13-0.0911%20 Aug →
inferno13–11-0.0715%20 Aug →
nuke7–13-0.0819%13 Aug →
nuke10–13-0.0511%13 Aug →
anubis6–13-0.064%25 Jun →
inferno13–8-0.0419%25 Jun →
inferno13–11-0.0715%18 Jun →
vertigo11–13-0.0910%18 Jun →
overpass12–16-0.0810%11 Jun →
ancient6–13-0.0718%11 Jun →
anubis4–13-0.0511%11 Jun →
ancient13–10-0.0831%21 May →
inferno13–8-0.0312%21 May →
nuke13–10-0.126%21 May →
dust222–25-0.0616%14 May →
nuke13–9-0.0921%14 May →
inferno8–13-0.0418%14 May →
inferno9–13-0.0815%7 May →
nuke13–11-0.0213%7 May →
ancient13–6-0.0514%23 Apr →
vertigo13–100.0320%23 Apr →
nuke13–4-0.057%23 Apr →
vertigo9–40.0418%19 Apr →
inferno4–9-0.1217%19 Apr →
nuke5–9-0.0811%19 Apr →
anubis13–11-0.0721%18 Apr →
inferno7–13-0.079%18 Apr →
ancient13–7-0.0726%18 Apr →
nuke3–13-0.1018%11 Dec →
ancient7–13-0.054%11 Dec →
inferno9–13-0.0810%11 Dec →
inferno13–11-0.0615%4 Dec →
ancient1–13-0.098%4 Dec →
nuke8–13-0.0516%4 Dec →
overpass13–11-0.058%4 Dec →
ancient5–13-0.0422%27 Nov →
inferno11–13-0.1021%27 Nov →
overpass9–130.0221%27 Nov →
overpass13–9-0.077%20 Nov →
train8–13-0.0814%20 Nov →
inferno4–13-0.1140%20 Nov →
ancient8–13-0.0716%20 Nov →
ancient11–13-0.0919%13 Nov →
mirage6–13-0.085%13 Nov →
inferno3–13-0.1518%13 Nov →
nuke13–1-0.0116%13 Nov →
overpass9–13-0.0810%6 Nov →
train13–8-0.065%6 Nov →
inferno9–13-0.0321%6 Nov →
inferno7–13-0.0510%23 Oct →
ancient13–10-0.0023%23 Oct →
nuke13–6-0.0410%9 Oct →
inferno11–13-0.066%9 Oct →
overpass8–13-0.1014%9 Oct →
ancient13–6-0.0913%2 Oct →
inferno13–3-0.0440%2 Oct →
vertigo13–11-0.039%2 Oct →
nuke13–80.0020%25 Sept →
overpass13–10-0.0513%18 Sept →
ancient19–17-0.049%18 Sept →
nuke9–13-0.107%4 Sept →
inferno13–8-0.0522%4 Sept →
mirage13–6-0.080%28 Aug →
inferno8–13-0.104%28 Aug →
nuke6–13-0.108%28 Aug →
vertigo10–13-0.0619%22 Aug →
ancient13–6-0.0315%21 Aug →
overpass13–80.014%21 Aug →
inferno16–18-0.099%14 Aug →
ancient16–14-0.0617%14 Aug →
inferno4–13-0.070%14 Aug →
anubis9–13-0.034%26 Jun →
nuke13–6-0.037%26 Jun →
anubis8–13-0.076%22 Jun →
ancient13–4-0.0910%22 Jun →
mirage0–130.000%22 Jun →
nuke8–13-0.0311%22 Jun →
inferno5–13-0.0711%19 Jun →
nuke13–100.0111%19 Jun →
anubis10–13-0.058%19 Jun →
anubis13–4-0.0750%12 Jun →
overpass9–13-0.0120%12 Jun →
inferno13–7-0.0115%12 Jun →
inferno7–13-0.0418%30 May →

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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