lovesosa — CS2 Stats
76561198083814536[U:1:123548808]
Rating over time
CSDB's own observations — this history builds from the day a profile is first viewed and cannot be backfilled.
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +0pp win rate · +0.04 avg rating
Player DNA
Primary style: Clutch Specialist — Late-round 1vX conversion well above par.
Strong CT-side openerReliable in 1v1s
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 89% playstyle similarity
Most alike: opening-fight frequency, opening-duel success.
Where you differ: 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 52% on CT to 32% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 632ms 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.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
| C | 47 | 18–29 | 38% | -0.00 | |
| D | 11 | 2–9 | 18% | -0.02 | |
| C | 10 | 4–6 | 40% | 0.02 | |
| D | 8 | 2–6 | 25% | -0.01 | |
| D | 7 | 1–6 | 14% | -0.04 | |
| S | 6 | 4–2 | 67% | 0.01 | |
| D | 5 | 1–4 | 20% | 0.00 | |
| — | 2 | 2–0 | 100% | 0.04 | |
| boulder | — | 1 | 1–0 | 100% | 0.01 |
| — | 1 | 1–0 | 100% | 0.05 | |
| office | — | 1 | 1–0 | 100% | 0.03 |
| — | 1 | 0–1 | 0% | -0.04 |
Across the last 100 tracked matches.
Mirage is currently your weakest sufficiently-sampled map (14% over 7). Start with the 6 essential Mirage 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.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWLLLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 8 | 50% | 0.92 | 13.5 |
| Inferno | 5 | 60% | 1.28 | 16.8 |
| Anubis | 4 | 75% | 1.09 | 19.0 |
| Vertigo | 4 | 75% | 1.28 | 13.3 |
| Dust2 | 3 | 67% | 0.59 | 10.0 |
| Overpass | 2 | 50% | 1.28 | 14.0 |
| Ancient | 2 | 50% | 0.62 | 10.0 |
| Nuke | 1 | 100% | 1.67 | 30.0 |
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.
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.
- 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 0.4112 — below the 0.5 mark we flag
- Advanced Mechanics
You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.
T opening duels 32.4009% — below the 40% mark we flag
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
14% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 10–13 | -0.06 | 22% | 25 Aug → | ||
| 5–13 | 0.06 | 24% | 24 Aug → | ||
| 12–12 | 0.06 | 20% | 22 Aug → | ||
| 3–13 | 0.01 | 16% | 22 Aug → | ||
| 8–13 | 0.04 | 20% | 20 Aug → | ||
| 6–13 | -0.05 | 20% | 20 Aug → | ||
| 13–8 | 0.05 | 29% | 18 Aug → | ||
| 9–13 | 0.01 | 20% | 18 Aug → | ||
| boulder | 13–9 | 0.01 | 19% | 18 Aug → | |
| 12–12 | -0.03 | 39% | 11 Aug → | ||
| 13–6 | -0.03 | 18% | 8 Aug → | ||
| 10–13 | -0.02 | 19% | 5 Aug → | ||
| 13–4 | 0.03 | 19% | 2 Aug → | ||
| 4–13 | -0.04 | 16% | 2 Aug → | ||
| 8–13 | -0.13 | 14% | 30 Jul → | ||
| 12–12 | -0.03 | 21% | 29 Jul → | ||
| 10–13 | -0.00 | 10% | 28 Jul → | ||
| 5–13 | -0.05 | 24% | 27 Jul → | ||
| 1–13 | -0.06 | 13% | 20 Jul → | ||
| 5–13 | -0.02 | 21% | 20 Jul → | ||
| 13–10 | 0.04 | 15% | 19 Jul → | ||
| 13–7 | 0.05 | 15% | 19 Jul → | ||
| 9–13 | 0.02 | 25% | 17 Jul → | ||
| 12–16 | -0.03 | 27% | 13 Jul → | ||
| 12–12 | -0.02 | 22% | 12 Jul → | ||
| 5–13 | -0.09 | 11% | 10 Jul → | ||
| 16–14 | -0.04 | 23% | 10 Jul → | ||
| 5–6 | 0.03 | 43% | 7 Jul → | ||
| 13–3 | 0.00 | 15% | 6 Jul → | ||
| 9–3 | 0.03 | 25% | 6 Jul → | ||
| 5–13 | -0.04 | 19% | 5 Jul → | ||
| 15–15 | -0.02 | 18% | 5 Jul → | ||
| 13–7 | 0.00 | 20% | 5 Jul → | ||
| 13–4 | 0.06 | 25% | 4 Jul → | ||
| 8–13 | 0.02 | 29% | 2 Jul → | ||
| 13–5 | 0.02 | 38% | 2 Jul → | ||
| 8–13 | -0.00 | 22% | 30 Jun → | ||
| 13–9 | 0.00 | 34% | 30 Jun → | ||
| 11–13 | -0.01 | 13% | 30 Jun → | ||
| 13–10 | -0.03 | 24% | 24 Jun → | ||
| 13–11 | 0.10 | 20% | 22 Jun → | ||
| 3–13 | -0.07 | 3% | 22 Jun → | ||
| 13–5 | 0.01 | 16% | 20 Jun → | ||
| 10–13 | 0.03 | 30% | 20 Jun → | ||
| 2–13 | -0.07 | 25% | 20 Jun → | ||
| 5–13 | -0.02 | 21% | 16 Jun → | ||
| 11–0 | -0.03 | 45% | 16 Jun → | ||
| 12–12 | -0.03 | 13% | 13 Jun → | ||
| 2–13 | -0.04 | 15% | 13 Jun → | ||
| 5–13 | -0.04 | 29% | 12 Jun → | ||
| 7–13 | 0.02 | 20% | 11 Jun → | ||
| 5–4 | 0.11 | 33% | 11 Jun → | ||
| office | 13–5 | 0.03 | 11% | 9 Jun → | |
| 13–4 | -0.05 | 13% | 9 Jun → | ||
| 9–13 | 0.00 | 11% | 9 Jun → | ||
| 13–10 | 0.03 | 17% | 6 Jun → | ||
| 14–16 | 0.04 | 20% | 3 Jun → | ||
| 12–12 | 0.04 | 24% | 3 Jun → | ||
| 3–11 | -0.04 | 17% | 3 Jun → | ||
| 12–12 | -0.01 | 16% | 3 Jun → | ||
| 2–13 | -0.06 | 17% | 31 May → | ||
| 5–13 | 0.03 | 19% | 30 May → | ||
| 13–5 | 0.07 | 32% | 29 May → | ||
| 10–13 | -0.03 | 9% | 27 May → | ||
| 11–13 | 0.02 | 16% | 27 May → | ||
| 3–13 | -0.02 | 11% | 22 May → | ||
| 7–13 | -0.06 | 8% | 20 May → | ||
| 12–12 | 0.01 | 29% | 20 May → | ||
| 6–13 | 0.02 | 22% | 20 May → | ||
| 13–8 | 0.02 | 8% | 19 May → | ||
| 10–13 | -0.04 | 12% | 19 May → | ||
| 15–15 | -0.01 | 18% | 18 May → | ||
| 13–16 | 0.01 | 17% | 18 May → | ||
| 2–13 | 0.00 | 32% | 17 May → | ||
| 6–13 | -0.06 | 20% | 17 May → | ||
| 13–1 | 0.07 | 13% | 17 May → | ||
| 13–3 | 0.05 | 21% | 16 May → | ||
| 3–13 | -0.02 | 15% | 15 May → | ||
| 13–5 | 0.03 | 36% | 13 May → | ||
| 13–9 | -0.08 | 14% | 10 May → | ||
| 12–12 | 0.10 | 22% | 10 May → | ||
| 13–6 | -0.04 | 20% | 10 May → | ||
| 13–10 | 0.02 | 18% | 8 May → | ||
| 13–7 | 0.06 | 18% | 6 May → | ||
| 13–5 | 0.01 | 16% | 5 May → | ||
| 13–11 | -0.07 | 23% | 5 May → | ||
| 13–3 | 0.03 | 29% | 4 May → | ||
| 13–11 | 0.01 | 25% | 1 May → | ||
| 1–13 | -0.09 | 21% | 1 May → | ||
| 13–10 | -0.01 | 11% | 1 May → | ||
| 13–16 | -0.01 | 7% | 29 Apr → | ||
| 4–13 | -0.04 | 13% | 29 Apr → | ||
| 11–13 | -0.00 | 16% | 29 Apr → | ||
| 13–7 | 0.04 | 15% | 29 Apr → | ||
| 9–13 | -0.09 | 9% | 28 Apr → | ||
| 13–2 | 0.11 | 7% | 25 Apr → | ||
| 10–13 | 0.00 | 20% | 25 Apr → | ||
| 13–11 | -0.02 | 3% | 21 Apr → | ||
| 10–13 | -0.06 | 24% | 21 Apr → | ||
| 15–15 | -0.01 | 25% | 21 Apr → |
Match data via Leetify.