RubydaSpooky

RubydaSpooky — CS2 Stats

76561198168737195[U:1:208471467]Steam profile ↗✓ No bans

3,727Tracked matches50%Win rate2020Tracked since
CSDB Rating5.7 SolidPositional Player
CSDB Leaderboard#98728 of 259663 tracked
FaceitLevel 9 · 1,969 ELOTop 20.7% of ranked FACEIT players
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 19,024 +1,905 28 Jan – 15 Feb · 8 days played
16,34719,722peak 19,72228 Jan15 Feb
19,722Peak Premier in tracked matches
1,969Highest Faceit ELO seen on CSDB
58Days played since 2025-11-02

Faceit ELO

  • At peak — 1,969
  • Next: Level 10 at 2,001 — 32 to go
  • Reached: Level 9 · Level 8 · Level 7 · Level 6

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

Share this profile

CSDB.GGRubydaSpookyFACEITLevel 9 · 1,969 ELOSTANDINGTop 20.7% of rankedPEAK ELO1,969csdb.gg/stats

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Performance scores

Aim63
Positioning79
Utility63

0–100 skill scores via Leetify.

Recent form

STEADY46–53–1Last 10046%Win rateWLWLWWLWWL

Last 10 vs previous 10: +10pp win rate · −0.03 avg rating · −0.1pp headshot accuracy · +40ms reaction

Win rate +10pp 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 -0.00
  • Avg headshot accuracy 17%
  • Avg reaction 500ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 17%
  • Avg reaction 541ms

Last 20

  • 11–9 · 55% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 18%
  • Avg reaction 521ms

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 (+2.2 against its own average).

Aim6.3
Utility6.3
Positioning7.9
Opening Duels5.7
Clutch2.8

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

device

Plays most like device 71% 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

Strengths

T openings. 65% T opening-duel success — entries that actually open the round.

Areas to improve

Counter-strafing. Only 61% 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

Aim6.3
Positioning7.9
Utility6.3
Mechanics2.5
Opening Duels7.6
Win Impact5.0

Composite 5.7/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01+0.03
first ⅓ avg -0.02 → last ⅓ avg 0.01
Reaction time529ms−84ms
first ⅓ avg 613ms → last ⅓ avg 529ms
Headshot accuracy19.5%−6.5%
first ⅓ avg 26.0% → last ⅓ avg 19.5%

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

0.09Best match rating · 13–9 · inferno, 17 Aug →
44%Best headshot accuracy · 5–12 · ancient, 3 Feb →
391msFastest reaction time · 9–13 · mirage, 21 Jan →
13–3Biggest win · cache, 10 Sept →

Across the last 100 tracked matches.

Highlights

5Longest win streak
10–10In matches decided by ≤2 rounds
9Overtime games

Map breakdown

mirageBest map · 53% over 17anubisWeakest map · 30% over 10
MapGradePlayedRecordWin rateAvg rating
ancientB2512–1348%0.00
infernoB2111–1052%0.00
mirageB179–853%0.01
dust2C135–838%-0.01
anubisD103–730%-0.03
cacheC52–340%0.01
overpass—43–175%0.01
nuke—31–233%-0.05
office—10–10%0.01
train—10–10%-0.07

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (30% over 10). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

4,593Matches
50%Win rate
1.00Avg K/D
77.3ADR
51%Headshot %

Clutches & streaks

34%1v1 clutch win
21%1v2 clutch win
13Longest win streak

Recent Faceit resultsLLLWL

MapMatchesWin rateAvg K/DAvg kills
Inferno42353%1.0015.7
Ancient40653%1.0016.2
Dust230449%0.9816.0
Mirage22840%0.9214.8
Anubis20647%0.9515.6
Nuke9746%0.9914.9
Overpass8656%0.9616.2
Vertigo2832%0.9216.1

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.

19.6%Headshot accuracy
32.7%Accuracy (enemy spotted)
36.8%Spray accuracy
61.3%Counter-strafing
9.1°Preaim
525msReaction time
65.3%T opening success
55.2%CT opening success
0.69Enemies flashed / flash
13.6%Flash assists
6.81HE damage / grenade
7.41Flashes / 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.

30% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache13–70.0319%28 Oct →
mirage5–13-0.0220%20 Oct →
mirage13–110.0216%19 Oct →
ancient10–13-0.0415%18 Oct →
inferno13–100.0114%18 Oct →
ancient13–60.0013%17 Oct →
anubis6–13-0.0130%17 Oct →
ancient13–110.0214%15 Oct →
ancient13–70.0516%15 Oct →
anubis14–16-0.0418%15 Oct →
dust211–13-0.0111%3 Oct →
ancient11–130.0817%3 Oct →
ancient13–50.0718%3 Oct →
ancient13–70.0117%3 Oct →
ancient3–130.0219%27 Sept →
inferno11–130.0322%27 Sept →
ancient7–130.0315%24 Sept →
inferno13–50.0617%18 Sept →
anubis13–60.0524%16 Sept →
ancient13–80.0117%15 Sept →
inferno10–130.0122%12 Sept →
cache13–3-0.0232%10 Sept →
dust216–14-0.0225%10 Sept →
anubis13–11-0.0121%10 Sept →
anubis14–16-0.0027%7 Sept →
dust27–13-0.0134%6 Sept →
cache6–130.0227%3 Sept →
ancient16–13-0.0018%3 Sept →
anubis10–13-0.0716%23 Aug →
cache4–13-0.0218%17 Aug →
inferno13–90.0914%17 Aug →
cache10–130.0618%17 Aug →
ancient9–13-0.0618%16 Aug →
inferno13–6-0.0023%15 Aug →
anubis4–13-0.0821%4 Mar →
inferno10–130.0731%3 Mar →
ancient8–13-0.0721%2 Mar →
dust26–130.0238%1 Mar →
inferno13–9-0.0015%1 Mar →
dust213–10-0.0526%1 Mar →
inferno13–10-0.0230%24 Feb →
anubis8–13-0.0822%22 Feb →
anubis7–13-0.0426%16 Feb →
mirage6–130.0125%15 Feb →
dust27–13-0.0538%15 Feb →
inferno13–70.0636%14 Feb →
mirage0–5-0.030%14 Feb →
inferno9–13-0.0122%14 Feb →
inferno11–13-0.0143%14 Feb →
inferno13–100.0428%14 Feb →
ancient13–110.0529%12 Feb →
mirage13–100.0326%12 Feb →
nuke16–130.0223%12 Feb →
ancient12–16-0.0333%12 Feb →
anubis13–7-0.0530%12 Feb →
ancient13–110.0723%12 Feb →
dust213–50.0543%11 Feb →
dust212–16-0.0119%11 Feb →
mirage3–10-0.0224%11 Feb →
ancient11–130.0627%11 Feb →
ancient5–12-0.0144%3 Feb →
inferno4–13-0.0717%30 Jan →
dust211–130.0337%30 Jan →
ancient13–90.0228%29 Jan →
mirage13–110.0725%29 Jan →
mirage13–4-0.0332%28 Jan →
mirage13–110.0229%28 Jan →
dust213–6-0.0422%28 Jan →
inferno5–8-0.0736%28 Jan →
office11–130.0131%27 Jan →
mirage13–90.0533%27 Jan →
mirage13–11-0.0424%23 Jan →
ancient4–13-0.0141%23 Jan →
mirage13–40.0630%22 Jan →
mirage9–130.0223%21 Jan →
mirage15–150.0421%17 Jan →
dust26–13-0.0423%13 Jan →
inferno7–13-0.0824%13 Jan →
mirage11–13-0.0241%10 Jan →
nuke3–13-0.107%10 Jan →
overpass8–130.0031%7 Jan →
train4–9-0.0729%21 Dec →
nuke8–13-0.0533%16 Dec →
overpass13–60.0531%13 Dec →
ancient13–5-0.0531%12 Dec →
mirage9–130.0234%12 Dec →
inferno13–7-0.0329%6 Dec →
ancient7–130.0217%6 Dec →
ancient6–13-0.0420%6 Dec →
ancient8–13-0.0432%5 Dec →
dust213–90.0113%2 Dec →
dust27–13-0.0125%29 Nov →
inferno13–4-0.0430%29 Nov →
inferno9–13-0.0024%28 Nov →
inferno8–13-0.0411%21 Nov →
mirage19–17-0.0323%18 Nov →
inferno13–70.0328%18 Nov →
overpass13–100.0520%11 Nov →
overpass13–10-0.0720%8 Nov →
ancient13–10-0.0621%2 Nov →

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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