SisterFister — CS2 Stats
76561198954805080[U:1:994539352]Steam profile ↗✓ No bans
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +30pp win rate · −0.01 avg rating · −2.2pp headshot accuracy · +32ms reaction
Win rate up 30pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (−0.01), so results shifted more than performance did.
Last 5 · 10 · 20 matches
Last 5
- 3–2 · 60% win rate
- Avg rating 0.02
- Avg headshot accuracy 17%
- Avg reaction 591ms
Last 10
- 7–3 · 70% win rate
- Avg rating 0.05
- Avg headshot accuracy 16%
- Avg reaction 594ms
Last 20
- 11–9 · 55% win rate
- Avg rating 0.05
- Avg headshot accuracy 18%
- Avg reaction 578ms
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: All-Rounder — No style dimension stands clear of the others in this profile.
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

Plays most like donk 63% playstyle similarity
Most alike: utility contribution, positioning profile.
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
Areas to improve
Reaction time. 642ms 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 5.3/10 (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 |
|---|---|---|---|---|---|
| B | 79 | 40–39 | 51% | 0.11 | |
| S | 9 | 6–3 | 67% | 0.13 | |
| — | 4 | 2–2 | 50% | -0.03 | |
| — | 3 | 3–0 | 100% | 0.02 | |
| — | 2 | 1–1 | 50% | -0.02 | |
| — | 2 | 1–1 | 50% | 0.01 | |
| — | 1 | 1–0 | 100% | 0.08 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (51% over 79). Start with the 6 essential Inferno 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 12.8923° — above the 12° mark we flag
- Grenades & UtilityGrenade Lineups →
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 2.6591 — below the 4 mark we flag
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 11–13 | -0.01 | 19% | 19 Oct → | ||
| 7–13 | -0.05 | 25% | 19 Oct → | ||
| 13–2 | 0.07 | 11% | 16 Oct → | ||
| 13–5 | 0.06 | 11% | 21 Sept → | ||
| 13–10 | -0.00 | 20% | 21 Sept → | ||
| 6–13 | -0.06 | 18% | 21 Sept → | ||
| 13–8 | 0.02 | 14% | 21 Sept → | ||
| 13–6 | 0.08 | 13% | 21 Sept → | ||
| 8–0 | 0.11 | 12% | 21 Sept → | ||
| 9–6 | 0.25 | 22% | 10 Sept → | ||
| 9–6 | 0.09 | 19% | 10 Sept → | ||
| 4–13 | -0.14 | 17% | 11 Aug → | ||
| 13–4 | -0.09 | 17% | 11 Aug → | ||
| 5–9 | 0.10 | 23% | 5 Jun → | ||
| 7–9 | 0.07 | 7% | 5 Jun → | ||
| 6–9 | 0.03 | 26% | 21 May → | ||
| 5–9 | 0.04 | 17% | 21 May → | ||
| 7–9 | 0.07 | 21% | 21 May → | ||
| 9–6 | 0.16 | 24% | 21 May → | ||
| 9–3 | 0.21 | 16% | 17 May → | ||
| 4–9 | 0.03 | 9% | 17 May → | ||
| 8–8 | 0.14 | 21% | 17 May → | ||
| 9–7 | 0.13 | 17% | 17 May → | ||
| 9–3 | 0.22 | 17% | 17 May → | ||
| 4–9 | -0.04 | 18% | 17 May → | ||
| 5–9 | -0.04 | 14% | 17 May → | ||
| 9–7 | 0.15 | 7% | 17 May → | ||
| 13–5 | 0.03 | 23% | 6 May → | ||
| 8–8 | 0.09 | 17% | 16 Apr → | ||
| 9–4 | 0.09 | 24% | 10 Apr → | ||
| 9–5 | 0.16 | 13% | 10 Apr → | ||
| 6–9 | 0.10 | 22% | 10 Apr → | ||
| 9–1 | 0.44 | 19% | 10 Apr → | ||
| 9–7 | 0.05 | 14% | 10 Apr → | ||
| 4–9 | 0.05 | 14% | 27 Mar → | ||
| 9–2 | 0.21 | 8% | 27 Mar → | ||
| 3–9 | -0.07 | 23% | 27 Mar → | ||
| 6–9 | 0.02 | 8% | 26 Mar → | ||
| 9–1 | 0.25 | 25% | 26 Mar → | ||
| 6–9 | 0.08 | 15% | 26 Mar → | ||
| 6–9 | 0.04 | 20% | 26 Mar → | ||
| 9–4 | 0.19 | 11% | 25 Mar → | ||
| 8–8 | 0.08 | 20% | 25 Mar → | ||
| 9–4 | 0.24 | 16% | 25 Mar → | ||
| 9–4 | 0.25 | 26% | 25 Mar → | ||
| 9–6 | 0.11 | 9% | 25 Mar → | ||
| 9–6 | 0.16 | 16% | 25 Mar → | ||
| 6–9 | 0.12 | 28% | 24 Mar → | ||
| 8–8 | 0.06 | 21% | 24 Mar → | ||
| 9–2 | 0.21 | 22% | 24 Mar → | ||
| 7–9 | 0.06 | 10% | 24 Mar → | ||
| 9–5 | 0.09 | 28% | 24 Mar → | ||
| 9–3 | 0.43 | 25% | 24 Mar → | ||
| 9–5 | 0.11 | 22% | 24 Mar → | ||
| 9–7 | 0.14 | 20% | 24 Mar → | ||
| 2–9 | -0.13 | 23% | 24 Mar → | ||
| 5–9 | -0.01 | 21% | 20 Mar → | ||
| 9–6 | 0.20 | 31% | 20 Mar → | ||
| 4–9 | -0.08 | 25% | 20 Mar → | ||
| 9–7 | 0.08 | 20% | 19 Mar → | ||
| 7–9 | 0.03 | 20% | 19 Mar → | ||
| 9–6 | 0.11 | 21% | 19 Mar → | ||
| 4–9 | -0.05 | 14% | 19 Mar → | ||
| 9–6 | 0.07 | 21% | 18 Mar → | ||
| 9–4 | 0.25 | 13% | 18 Mar → | ||
| 9–1 | 0.33 | 22% | 17 Mar → | ||
| 8–8 | 0.17 | 25% | 17 Mar → | ||
| 4–9 | -0.11 | 10% | 17 Mar → | ||
| 8–8 | 0.08 | 17% | 16 Mar → | ||
| 9–3 | 0.31 | 21% | 16 Mar → | ||
| 4–9 | 0.02 | 16% | 16 Mar → | ||
| 9–5 | 0.17 | 21% | 16 Mar → | ||
| 8–8 | 0.14 | 23% | 15 Mar → | ||
| 6–9 | -0.08 | 13% | 15 Mar → | ||
| 8–8 | 0.07 | 22% | 15 Mar → | ||
| 9–6 | 0.20 | 22% | 15 Mar → | ||
| 9–5 | 0.30 | 15% | 15 Mar → | ||
| 3–9 | -0.11 | 28% | 14 Mar → | ||
| 8–8 | 0.13 | 24% | 14 Mar → | ||
| 9–2 | 0.25 | 39% | 14 Mar → | ||
| 6–9 | 0.03 | 15% | 14 Mar → | ||
| 13–7 | -0.04 | 20% | 26 Feb → | ||
| 4–9 | 0.02 | 14% | 15 Feb → | ||
| 9–7 | 0.13 | 18% | 15 Feb → | ||
| 9–7 | 0.14 | 18% | 15 Feb → | ||
| 9–6 | 0.13 | 15% | 15 Feb → | ||
| 8–8 | 0.17 | 27% | 15 Feb → | ||
| 3–9 | -0.04 | 20% | 15 Feb → | ||
| 9–2 | 0.25 | 21% | 14 Feb → | ||
| 9–5 | 0.10 | 17% | 14 Feb → | ||
| 9–1 | 0.31 | 18% | 14 Feb → | ||
| 9–4 | 0.26 | 19% | 14 Feb → | ||
| 8–8 | 0.02 | 19% | 10 Feb → | ||
| 9–5 | 0.14 | 21% | 10 Feb → | ||
| 9–3 | 0.26 | 17% | 10 Feb → | ||
| 2–9 | -0.08 | 18% | 10 Feb → | ||
| 9–2 | 0.21 | 24% | 8 Feb → | ||
| 8–8 | 0.25 | 20% | 8 Feb → | ||
| 9–6 | 0.07 | 18% | 8 Feb → | ||
| 7–9 | 0.02 | 17% | 8 Feb → |
Match data via Leetify.
Recent teammates
Milestones
This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.