esa — CS2 Stats
76561197973043734[U:1:12778006]Steam profile ↗✓ No bans
Rating over time
Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +10pp win rate · +0.02 avg rating · +1.7pp headshot accuracy · −12ms 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 15%
- Avg reaction 650ms
Last 10
- 5–5 · 50% win rate
- Avg rating -0.01
- Avg headshot accuracy 15%
- Avg reaction 647ms
Last 20
- 9–11 · 45% win rate
- Avg rating -0.02
- Avg headshot accuracy 14%
- Avg reaction 653ms
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 (+1.7 against its own average).
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
Plays most like s1mple 81% playstyle similarity
Most alike: positioning profile, opening-duel success.
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. 659ms 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
Composite 4.9/10 (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
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
Across the last 100 tracked matches.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
 anubis | D | 21 | 6–15 | 29% | -0.02 |
 ancient | S | 20 | 13–7 | 65% | -0.02 |
 nuke | A | 19 | 12–7 | 63% | -0.01 |
 inferno | B | 17 | 8–9 | 47% | -0.01 |
 train | B | 11 | 5–6 | 45% | -0.03 |
 dust2 | C | 8 | 3–5 | 38% | -0.02 |
 overpass | — | 3 | 1–2 | 33% | -0.01 |
 mirage | — | 1 | 0–1 | 0% | -0.13 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (29% over 21). 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 12.2664° — 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 13.3864% — 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.
29% win rate across 21 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| dust2 | 13–3 | 0.02 | 7% | 10 Apr → | |
| ancient | 8–13 | -0.02 | 26% | 10 Apr → | |
| overpass | 13–3 | 0.01 | 10% | 29 Jul → | |
| overpass | 9–13 | -0.01 | 9% | 24 Jul → | |
| ancient | 13–11 | -0.00 | 25% | 24 Jul → | |
| dust2 | 13–11 | 0.02 | 8% | 10 Jul → | |
| inferno | 13–11 | 0.03 | 22% | 10 Jul → | |
| train | 7–13 | -0.03 | 15% | 4 Jul → | |
| anubis | 9–13 | -0.06 | 10% | 3 Jul → | |
| ancient | 8–13 | -0.04 | 15% | 3 Jul → | |
| train | 13–10 | -0.05 | 8% | 1 Jul → | |
| inferno | 7–13 | -0.01 | 22% | 1 Jul → | |
| anubis | 13–10 | 0.02 | 10% | 17 Jun → | |
| dust2 | 3–13 | -0.05 | 26% | 17 Jun → | |
| inferno | 6–13 | 0.01 | 13% | 11 Jun → | |
| inferno | 13–5 | -0.01 | 16% | 11 Jun → | |
| anubis | 6–13 | -0.02 | 5% | 11 Jun → | |
| ancient | 6–13 | -0.01 | 13% | 11 Jun → | |
| nuke | 13–11 | -0.03 | 14% | 10 Jun → | |
| anubis | 5–13 | -0.07 | 3% | 10 Jun → | |
| ancient | 13–11 | -0.05 | 16% | 9 Jun → | |
| nuke | 11–13 | -0.07 | 9% | 9 Jun → | |
| anubis | 13–11 | -0.02 | 12% | 9 Jun → | |
| ancient | 13–10 | -0.00 | 18% | 8 Jun → | |
| inferno | 16–14 | -0.00 | 12% | 8 Jun → | |
| ancient | 7–13 | -0.08 | 12% | 5 Jun → | |
| train | 7–13 | -0.03 | 10% | 4 Jun → | |
| inferno | 13–10 | 0.06 | 15% | 4 Jun → | |
| nuke | 13–10 | -0.01 | 8% | 4 Jun → | |
| anubis | 11–13 | -0.01 | 11% | 4 Jun → | |
| anubis | 6–13 | -0.06 | 13% | 4 Jun → | |
| inferno | 2–13 | -0.11 | 13% | 4 Jun → | |
| nuke | 13–3 | -0.07 | 11% | 3 Jun → | |
| anubis | 10–13 | -0.06 | 19% | 3 Jun → | |
| nuke | 13–10 | 0.04 | 13% | 3 Jun → | |
| ancient | 10–13 | -0.02 | 7% | 3 Jun → | |
| mirage | 2–13 | -0.13 | 0% | 2 Jun → | |
| anubis | 8–13 | -0.03 | 13% | 2 Jun → | |
| nuke | 13–6 | -0.02 | 10% | 2 Jun → | |
| ancient | 13–6 | -0.02 | 11% | 2 Jun → | |
| train | 13–4 | 0.07 | 13% | 1 Jun → | |
| dust2 | 13–1 | 0.02 | 9% | 1 Jun → | |
| nuke | 13–9 | -0.02 | 18% | 1 Jun → | |
| nuke | 10–13 | -0.03 | 13% | 1 Jun → | |
| inferno | 6–13 | -0.10 | 16% | 1 Jun → | |
| anubis | 15–15 | -0.02 | 3% | 31 May → | |
| ancient | 13–10 | -0.07 | 12% | 31 May → | |
| inferno | 13–8 | 0.03 | 22% | 31 May → | |
| nuke | 11–13 | -0.03 | 27% | 31 May → | |
| overpass | 10–13 | -0.04 | 12% | 30 May → | |
| dust2 | 3–13 | -0.05 | 16% | 30 May → | |
| ancient | 7–13 | -0.06 | 9% | 30 May → | |
| anubis | 13–6 | 0.01 | 6% | 29 May → | |
| nuke | 8–13 | -0.06 | 20% | 29 May → | |
| anubis | 13–1 | 0.05 | 13% | 26 May → | |
| train | 13–7 | -0.08 | 14% | 26 May → | |
| ancient | 13–9 | 0.00 | 3% | 26 May → | |
| train | 12–6 | -0.05 | 8% | 21 May → | |
| anubis | 14–16 | 0.00 | 10% | 20 May → | |
| train | 13–16 | -0.03 | 21% | 20 May → | |
| ancient | 13–9 | 0.00 | 7% | 20 May → | |
| anubis | 5–13 | -0.03 | 17% | 20 May → | |
| ancient | 4–13 | -0.08 | 0% | 20 May → | |
| inferno | 8–13 | -0.06 | 23% | 19 May → | |
| ancient | 13–3 | 0.09 | 11% | 19 May → | |
| nuke | 13–9 | 0.08 | 20% | 19 May → | |
| dust2 | 4–13 | -0.03 | 10% | 16 May → | |
| train | 3–13 | -0.06 | 8% | 16 May → | |
| nuke | 14–16 | -0.02 | 11% | 16 May → | |
| inferno | 2–13 | -0.02 | 14% | 16 May → | |
| anubis | 13–5 | 0.15 | 16% | 16 May → | |
| anubis | 13–3 | -0.02 | 10% | 16 May → | |
| ancient | 13–2 | 0.03 | 8% | 16 May → | |
| anubis | 5–13 | -0.03 | 9% | 15 May → | |
| nuke | 13–9 | 0.01 | 11% | 15 May → | |
| inferno | 6–13 | -0.01 | 12% | 15 May → | |
| inferno | 11–13 | 0.05 | 21% | 13 May → | |
| ancient | 13–10 | 0.03 | 13% | 13 May → | |
| nuke | 16–14 | 0.04 | 17% | 13 May → | |
| inferno | 13–3 | -0.03 | 19% | 13 May → | |
| anubis | 13–16 | 0.01 | 19% | 13 May → | |
| dust2 | 8–13 | -0.05 | 22% | 10 May → | |
| anubis | 5–13 | -0.08 | 9% | 10 May → | |
| ancient | 13–10 | -0.03 | 11% | 10 May → | |
| dust2 | 12–16 | -0.02 | 22% | 9 May → | |
| nuke | 10–13 | 0.01 | 13% | 9 May → | |
| train | 9–13 | -0.03 | 20% | 9 May → | |
| ancient | 13–8 | -0.02 | 7% | 9 May → | |
| nuke | 12–6 | -0.02 | 18% | 9 May → | |
| inferno | 13–4 | 0.01 | 11% | 9 May → | |
| nuke | 13–4 | -0.05 | 8% | 8 May → | |
| train | 14–16 | 0.01 | 16% | 8 May → | |
| ancient | 13–7 | 0.00 | 20% | 8 May → | |
| anubis | 9–13 | -0.03 | 10% | 8 May → | |
| inferno | 13–9 | 0.00 | 17% | 7 May → | |
| nuke | 13–4 | 0.02 | 24% | 7 May → | |
| anubis | 3–13 | -0.11 | 3% | 7 May → | |
| nuke | 11–13 | -0.02 | 9% | 7 May → | |
| train | 13–7 | -0.03 | 9% | 7 May → | |
| inferno | 11–13 | -0.05 | 21% | 7 May → |
Match data via Leetify.
Recent teammates
Milestones
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