joy89 — CS2 Stats
US76561198349954337[U:1:389688609]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Grey band among CSDB-tracked players (n=369), 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.
| Metric | This player | Grey band median | Light Blue band median | vs Light Blue band |
|---|---|---|---|---|
| Headshot rate | 30.5% | 37.5% | 39.7% | 9.2% short |
| Shot accuracy | 0.0% | 4.5% | 6.7% | 6.7% short |
| Kill/death ratio | 0.76 | 0.82 | 0.91 | 0.14 short |
| Match win rate | 33.1% | 39.1% | 42.1% | 9.0% short |
This profile sits below the typical Light Blue band player on every metric we can compare.
Widest gap: Shot accuracy. That is the metric furthest from the Light Blue band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -20pp win rate · +0.00 avg rating
Player DNA
Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.
Your pro match

Plays most like b1t 77% playstyle similarity
Most alike: opening-fight frequency, opening-duel success.
Where you differ: lower positioning profile; 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 48% on CT to 32% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 695ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.
Counter-strafing. Only 50% 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
Composite 2.8/10 (Learning), 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
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.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
| B | 24 | 11–13 | 46% | -0.01 | |
| B | 15 | 8–7 | 53% | -0.02 | |
| A | 14 | 8–6 | 57% | -0.01 | |
| C | 13 | 5–8 | 38% | -0.03 | |
| A | 7 | 4–3 | 57% | -0.04 | |
| B | 6 | 3–3 | 50% | -0.06 | |
| office | S | 6 | 5–1 | 83% | -0.01 |
| S | 6 | 4–2 | 67% | 0.01 | |
| — | 4 | 1–3 | 25% | -0.05 | |
| — | 3 | 2–1 | 67% | -0.03 | |
| — | 1 | 0–1 | 0% | 0.03 | |
| poseidon | — | 1 | 0–1 | 0% | -0.17 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (38% over 13). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.
Lifetime stats
Most-used weapons
Lifetime map wins
Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.
Skill profile
Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.
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.
- Advanced MechanicsAim Training →
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 13.0579° — above the 12° mark we flag
- Best CS2 CrosshairAim Training →
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 11.1715% — below the 15% mark we flag
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 13 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 8–13 | -0.08 | 4% | 30 Jun → | ||
| 11–13 | -0.11 | 3% | 29 Jun → | ||
| 13–9 | 0.08 | 12% | 28 Jun → | ||
| 11–13 | -0.05 | 14% | 23 Jun → | ||
| 13–7 | -0.03 | 11% | 23 Jun → | ||
| 0–13 | -0.06 | 13% | 23 Jun → | ||
| 5–2 | -0.04 | 11% | 23 Jun → | ||
| 13–2 | -0.05 | 16% | 23 Jun → | ||
| 12–12 | 0.03 | 11% | 9 Jun → | ||
| 9–13 | -0.06 | 15% | 9 Jun → | ||
| 12–12 | -0.00 | 29% | 9 Jun → | ||
| 13–4 | 0.11 | 10% | 9 Jun → | ||
| office | 13–11 | -0.09 | 21% | 9 Jun → | |
| poseidon | 4–9 | -0.17 | 20% | 5 Jun → | |
| 0–9 | -0.29 | 0% | 5 Jun → | ||
| 13–11 | 0.03 | 8% | 5 Jun → | ||
| 9–6 | 0.08 | 12% | 5 Jun → | ||
| 13–6 | -0.02 | 14% | 4 Jun → | ||
| 9–6 | -0.03 | 14% | 4 Jun → | ||
| 8–8 | -0.03 | 23% | 4 Jun → | ||
| 2–9 | -0.18 | 20% | 4 Jun → | ||
| 9–3 | 0.09 | 8% | 4 Jun → | ||
| 13–6 | 0.03 | 2% | 3 Jun → | ||
| 13–2 | 0.05 | 6% | 2 Jun → | ||
| 13–11 | 0.02 | 18% | 2 Jun → | ||
| 6–13 | -0.07 | 0% | 2 Jun → | ||
| 3–13 | -0.00 | 3% | 2 Jun → | ||
| 5–13 | 0.06 | 9% | 2 Jun → | ||
| 8–13 | -0.10 | 8% | 25 May → | ||
| 13–9 | -0.07 | 7% | 25 May → | ||
| 13–7 | 0.06 | 15% | 12 May → | ||
| 13–8 | -0.02 | 4% | 12 May → | ||
| 9–13 | -0.01 | 17% | 12 May → | ||
| office | 12–12 | -0.04 | 12% | 11 May → | |
| 5–2 | -0.10 | 33% | 11 May → | ||
| 13–2 | -0.06 | 13% | 11 May → | ||
| 7–13 | -0.06 | 4% | 11 May → | ||
| office | 13–11 | -0.01 | 10% | 9 May → | |
| 13–11 | 0.03 | 7% | 8 May → | ||
| 7–13 | -0.08 | 13% | 8 May → | ||
| 13–7 | -0.02 | 9% | 8 May → | ||
| 13–10 | 0.05 | 9% | 7 May → | ||
| 16–12 | 0.01 | 8% | 7 May → | ||
| office | 7–3 | 0.11 | 13% | 7 May → | |
| 13–4 | -0.00 | 17% | 7 May → | ||
| 12–12 | -0.04 | 17% | 7 May → | ||
| 9–13 | -0.09 | 8% | 7 May → | ||
| office | 13–6 | -0.07 | 6% | 7 May → | |
| 13–5 | -0.07 | 10% | 7 May → | ||
| 2–13 | -0.07 | 7% | 6 May → | ||
| 13–3 | -0.01 | 5% | 6 May → | ||
| 13–8 | -0.04 | 3% | 6 May → | ||
| 12–12 | -0.05 | 6% | 6 May → | ||
| office | 13–6 | 0.04 | 6% | 6 May → | |
| 12–12 | -0.04 | 9% | 6 May → | ||
| 13–8 | -0.08 | 21% | 6 May → | ||
| 13–16 | 0.00 | 10% | 5 May → | ||
| 13–5 | -0.01 | 25% | 5 May → | ||
| 1–10 | -0.01 | 7% | 4 May → | ||
| 3–13 | 0.01 | 6% | 4 May → | ||
| 13–11 | -0.04 | 7% | 3 May → | ||
| 13–7 | -0.01 | 13% | 3 May → | ||
| 12–12 | -0.09 | 14% | 3 May → | ||
| 13–2 | 0.06 | 8% | 3 May → | ||
| 13–8 | -0.04 | 16% | 3 May → | ||
| 6–13 | -0.04 | 14% | 29 Apr → | ||
| 13–5 | 0.02 | 16% | 29 Apr → | ||
| 13–10 | 0.04 | 11% | 29 Apr → | ||
| 11–13 | 0.05 | 10% | 29 Apr → | ||
| 13–3 | 0.04 | 15% | 24 Apr → | ||
| 13–7 | -0.00 | 14% | 24 Apr → | ||
| 13–7 | -0.04 | 11% | 24 Apr → | ||
| 9–13 | -0.08 | 7% | 24 Apr → | ||
| 8–13 | 0.06 | 14% | 24 Apr → | ||
| 4–13 | -0.03 | 12% | 24 Apr → | ||
| 12–16 | -0.04 | 21% | 22 Apr → | ||
| 13–7 | 0.01 | 19% | 22 Apr → | ||
| 8–13 | -0.01 | 7% | 22 Apr → | ||
| 13–11 | -0.00 | 6% | 22 Apr → | ||
| 13–7 | -0.02 | 4% | 20 Apr → | ||
| 7–13 | -0.07 | 3% | 20 Apr → | ||
| 5–13 | -0.06 | 4% | 20 Apr → | ||
| 2–13 | -0.02 | 10% | 20 Apr → | ||
| 13–11 | -0.05 | 6% | 20 Apr → | ||
| 8–13 | 0.05 | 11% | 20 Apr → | ||
| 3–13 | 0.03 | 8% | 19 Apr → | ||
| 13–6 | -0.10 | 12% | 19 Apr → | ||
| 13–6 | 0.04 | 17% | 19 Apr → | ||
| 13–9 | -0.01 | 7% | 19 Apr → | ||
| 13–7 | -0.02 | 5% | 19 Apr → | ||
| 10–13 | -0.03 | 12% | 19 Apr → | ||
| 9–13 | -0.06 | 17% | 18 Apr → | ||
| 13–6 | 0.01 | 6% | 18 Apr → | ||
| 2–13 | -0.06 | 0% | 18 Apr → | ||
| 6–13 | 0.05 | 9% | 17 Apr → | ||
| 11–13 | 0.01 | 11% | 17 Apr → | ||
| 10–13 | -0.07 | 36% | 17 Apr → | ||
| 7–13 | -0.05 | 4% | 17 Apr → | ||
| 11–13 | -0.06 | 7% | 17 Apr → | ||
| 11–13 | 0.04 | 10% | 17 Apr → |
Match data via Leetify.