macbeth10 — CS2 Stats
76561198273483047[U:1:313217319]
Share this profile
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
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +20pp win rate · -0.03 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 NiKo 58% playstyle similarity
Most alike: opening-duel success, positioning profile.
Where you differ: lower opening-fight frequency; 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 30% on CT to 15% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 691ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.
Counter-strafing. Only 57% 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 1.4/10 (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 |
|---|---|---|---|---|---|
 inferno | B | 23 | 11–12 | 48% | -0.02 |
 nuke | D | 19 | 5–14 | 26% | -0.03 |
 anubis | D | 15 | 1–14 | 7% | -0.04 |
 ancient | A | 15 | 9–6 | 60% | -0.04 |
 cache | D | 9 | 3–6 | 33% | -0.05 |
 dust2 | D | 9 | 3–6 | 33% | -0.03 |
 mirage | — | 3 | 1–2 | 33% | -0.07 |
 overpass | — | 3 | 2–1 | 67% | -0.04 |
 vertigo | — | 2 | 0–2 | 0% | -0.06 |
| warden | — | 1 | 0–1 | 0% | 0.01 |
 train | — | 1 | 0–1 | 0% | -0.04 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (7% over 15). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.
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 12.0571° — 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 10.8076% — below the 15% mark we flag
- Grenades & UtilityGrenade Lineups →
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.2839 — below the 0.5 mark we flag
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
7% win rate across 15 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| cache | 5–13 | -0.11 | 6% | 22 Aug → | |
| anubis | 8–13 | -0.07 | 6% | 22 Aug → | |
| nuke | 10–13 | -0.08 | 11% | 22 Aug → | |
| cache | 13–10 | -0.01 | 11% | 21 Aug → | |
| ancient | 13–7 | -0.07 | 9% | 21 Aug → | |
| anubis | 6–13 | -0.00 | 8% | 21 Aug → | |
| inferno | 13–11 | 0.01 | 25% | 21 Aug → | |
| anubis | 3–13 | -0.06 | 8% | 20 Aug → | |
| ancient | 13–6 | -0.08 | 10% | 20 Aug → | |
| nuke | 7–13 | -0.01 | 12% | 17 Aug → | |
| inferno | 13–6 | 0.06 | 6% | 17 Aug → | |
| inferno | 7–13 | -0.01 | 14% | 17 Aug → | |
| ancient | 8–13 | 0.00 | 15% | 13 Aug → | |
| nuke | 11–13 | -0.02 | 12% | 11 Aug → | |
| nuke | 9–13 | -0.04 | 7% | 11 Aug → | |
| anubis | 2–13 | -0.04 | 8% | 11 Aug → | |
| ancient | 2–13 | -0.08 | 4% | 10 Aug → | |
| nuke | 9–13 | -0.02 | 2% | 10 Aug → | |
| cache | 13–9 | -0.09 | 10% | 10 Aug → | |
| dust2 | 15–15 | -0.00 | 24% | 6 Aug → | |
| anubis | 13–5 | -0.04 | 11% | 19 Jul → | |
| ancient | 5–13 | -0.07 | 15% | 19 Jul → | |
| inferno | 14–16 | 0.03 | 13% | 18 Jul → | |
| ancient | 13–9 | -0.01 | 15% | 14 Jul → | |
| inferno | 13–7 | 0.04 | 6% | 14 Jul → | |
| anubis | 14–16 | -0.07 | 6% | 14 Jul → | |
| anubis | 9–13 | 0.00 | 12% | 13 Jul → | |
| cache | 11–13 | -0.04 | 11% | 13 Jul → | |
| inferno | 13–9 | -0.01 | 10% | 13 Jul → | |
| cache | 5–13 | -0.03 | 8% | 12 Jul → | |
| dust2 | 11–13 | -0.02 | 15% | 12 Jul → | |
| ancient | 4–7 | -0.07 | 29% | 10 Jul → | |
| cache | 13–10 | 0.01 | 11% | 10 Jul → | |
| anubis | 8–13 | 0.03 | 8% | 10 Jul → | |
| inferno | 13–6 | -0.05 | 10% | 9 Jul → | |
| nuke | 13–8 | -0.04 | 11% | 9 Jul → | |
| nuke | 11–13 | -0.01 | 15% | 9 Jul → | |
| cache | 6–13 | -0.06 | 7% | 9 Jul → | |
| vertigo | 2–13 | -0.07 | 8% | 8 Jul → | |
| cache | 6–13 | -0.06 | 4% | 8 Jul → | |
| dust2 | 2–13 | -0.09 | 26% | 8 Jul → | |
| inferno | 13–11 | 0.01 | 17% | 8 Jul → | |
| anubis | 1–13 | -0.13 | 17% | 8 Jul → | |
| vertigo | 11–13 | -0.04 | 6% | 7 Jul → | |
| warden | 10–13 | 0.01 | 8% | 7 Jul → | |
| cache | 5–13 | -0.05 | 8% | 7 Jul → | |
| train | 5–13 | -0.04 | 14% | 7 Jul → | |
| ancient | 11–13 | 0.01 | 12% | 6 Jul → | |
| anubis | 10–13 | -0.02 | 12% | 6 Jul → | |
| nuke | 7–13 | -0.05 | 7% | 6 Jul → | |
| anubis | 10–13 | -0.04 | 14% | 5 Jul → | |
| nuke | 5–13 | 0.01 | 28% | 5 Jul → | |
| inferno | 7–13 | -0.06 | 11% | 5 Jul → | |
| dust2 | 13–5 | 0.01 | 9% | 29 Jun → | |
| dust2 | 14–16 | -0.04 | 10% | 29 Jun → | |
| mirage | 7–13 | -0.10 | 18% | 29 Jun → | |
| inferno | 13–10 | 0.00 | 10% | 9 Jun → | |
| inferno | 7–13 | -0.14 | 10% | 9 Jun → | |
| inferno | 5–13 | -0.04 | 14% | 8 Jun → | |
| ancient | 13–6 | -0.10 | 16% | 8 Jun → | |
| dust2 | 11–13 | -0.03 | 2% | 8 Jun → | |
| inferno | 7–13 | -0.05 | 4% | 6 Jun → | |
| nuke | 5–13 | -0.06 | 10% | 6 Jun → | |
| ancient | 9–3 | -0.05 | 9% | 6 Jun → | |
| inferno | 13–9 | -0.00 | 5% | 4 Jun → | |
| nuke | 13–9 | -0.08 | 3% | 4 Jun → | |
| ancient | 13–10 | 0.03 | 4% | 2 Jun → | |
| ancient | 13–10 | -0.01 | 11% | 2 Jun → | |
| overpass | 14–16 | -0.01 | 8% | 1 Jun → | |
| inferno | 4–13 | -0.11 | 0% | 1 Jun → | |
| nuke | 9–13 | -0.01 | 20% | 1 Jun → | |
| mirage | 6–13 | -0.05 | 3% | 29 May → | |
| inferno | 3–13 | -0.04 | 8% | 29 May → | |
| nuke | 13–11 | -0.03 | 2% | 28 May → | |
| mirage | 13–9 | -0.06 | 3% | 28 May → | |
| anubis | 7–13 | -0.02 | 9% | 27 May → | |
| overpass | 13–7 | -0.06 | 3% | 26 May → | |
| inferno | 5–13 | 0.01 | 10% | 26 May → | |
| dust2 | 13–5 | -0.00 | 10% | 25 May → | |
| dust2 | 6–13 | -0.11 | 5% | 25 May → | |
| dust2 | 13–5 | 0.05 | 9% | 25 May → | |
| nuke | 12–16 | 0.00 | 10% | 19 May → | |
| inferno | 7–13 | 0.04 | 11% | 18 May → | |
| nuke | 9–13 | -0.03 | 11% | 18 May → | |
| nuke | 13–2 | 0.05 | 7% | 17 May → | |
| overpass | 13–6 | -0.04 | 0% | 17 May → | |
| ancient | 13–5 | -0.06 | 11% | 17 May → | |
| ancient | 13–5 | 0.05 | 10% | 17 May → | |
| inferno | 11–13 | -0.01 | 7% | 13 May → | |
| inferno | 13–7 | -0.05 | 4% | 13 May → | |
| anubis | 3–13 | -0.05 | 10% | 12 May → | |
| ancient | 5–13 | -0.08 | 3% | 12 May → | |
| nuke | 1–13 | -0.05 | 4% | 12 May → | |
| anubis | 11–13 | 0.01 | 7% | 11 May → | |
| inferno | 13–10 | -0.01 | 2% | 11 May → | |
| nuke | 16–12 | -0.03 | 11% | 9 May → | |
| inferno | 1–13 | 0.00 | 16% | 9 May → | |
| inferno | 13–5 | -0.01 | 2% | 6 May → | |
| nuke | 10–13 | -0.01 | 10% | 5 May → | |
| anubis | 8–13 | -0.01 | 5% | 4 May → |
Match data via Leetify.
