-=]Fraggel[=-trickpa

-=]Fraggel[=-trickpa — CS2 Stats

DE76561197960516734[U:1:251006]Steam profile ↗✓ No bans

1,074Tracked matches52%Win rate2023Tracked since
CSDB Rating4.7 DevelopingPositional Player
Premier CS Rating4,646Grey band · top ~80.3% of ranked players (population est.)
WingmanGold Nova I
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 30 Sep 2026 (yesterday). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 4,646 -1,735 31 Aug – 30 Sept · 26 days played
3,6106,381peak 6,38131 Aug30 Sept
6,565Peak Premier in tracked matches
25Days played since 2026-08-31

Premier CS Rating

  • 1,735 below peak (6,381)
  • -1,735 over 30 days · declining
  • Next: Light Blue band at 5,000 — 354 to go
  • Reached: Light Blue band
  • Light Blue band first seen 2026-08-31

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Share this profile

CSDB.GG-=]Fraggel[=-trickpaPREMIER4,646 · Grey bandcsdb.gg/stats

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Performance scores

Aim44
Positioning60
Utility46

0–100 skill scores via Leetify.

Recent form

STEADY43–54–3Last 10043%Win rateLWWWLLWTWW

Last 10 vs previous 10: +20pp win rate · −0.00 avg rating · −4.2pp headshot accuracy · +12ms reaction

Win rate up 20pp 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 (−0.00), 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 7%
  • Avg reaction 631ms

Last 10

  • 6–3–1 · 60% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 9%
  • Avg reaction 662ms

Last 20

  • 10–9–1 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 12%
  • Avg reaction 657ms

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 (+1.2 against its own average).

Aim4.4
Utility4.6
Positioning6.0
Opening Duels3.7

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

jL

Plays most like jL 71% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution; 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

Strengths

T openings. 70% T opening-duel success — entries that actually open the round.

Areas to improve

CT openings. Opening success drops from 70% on T to 44% on CT — first contacts on the defending side are being lost.

Reaction time. 671ms 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

Aim4.4
Positioning6.0
Utility4.6
Mechanics5.3
Opening Duels6.7
Win Impact5.6

Composite 4.7/10 (Developing), 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

Match rating-0.00+0.01
first ⅓ avg -0.01 → last ⅓ avg -0.00
Reaction time680ms+14ms
first ⅓ avg 666ms → last ⅓ avg 680ms
Headshot accuracy11.1%+1.7%
first ⅓ avg 9.4% → last ⅓ avg 11.1%

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

0.14Best match rating · 13–7 · dust2, 25 Sept →
46%Best headshot accuracy · 0–12 · vertigo, 11 Sept →
406msFastest reaction time · 8–13 · office, 25 Sept →
13–2Biggest win · vertigo, 25 Sept →

Across the last 100 tracked matches.

Highlights

4Longest win streak
4–3In matches decided by ≤2 rounds
4Overtime games

Map breakdown

vertigoBest map · 60% over 5ancientWeakest map · 22% over 9
MapGradePlayedRecordWin rateAvg rating
dust2B3115–1648%0.01
infernoC167–944%-0.02
nukeA116–555%0.01
cacheD113–827%-0.00
ancientD92–722%-0.00
mirageD82–625%-0.01
vertigoA53–260%0.00
office—31–233%-0.06
anubis—31–233%-0.03
train—22–0100%0.08
shelter—11–0100%-0.02

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (22% over 9). Start with the 6 essential Ancient 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.

11.1%Headshot accuracy
34.8%Accuracy (enemy spotted)
41.0%Spray accuracy
73.7%Counter-strafing
11.9°Preaim
671msReaction time
69.7%T opening success
44.0%CT opening success
0.58Enemies flashed / flash
3.3%Flash assists
10.62HE damage / grenade
1.89Flashes / match

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.

  1. Best CS2 Crosshair

    Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.

    Headshot accuracy 11.0704% — below the 15% mark we flag

    Aim Training →
  2. Grenades & Utility

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 1.8903 — below the 4 mark we flag

    Grenade Lineups →
Spend your practice time on Ancient

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

22% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno9–13-0.089%30 Sept →
dust213–100.005%30 Sept →
inferno13–8-0.036%30 Sept →
nuke13–60.036%30 Sept →
ancient5–13-0.016%30 Sept →
mirage7–13-0.0515%29 Sept →
inferno16–14-0.058%29 Sept →
ancient15–15-0.017%29 Sept →
dust216–13-0.0215%29 Sept →
inferno13–30.0716%28 Sept →
mirage13–6-0.0520%28 Sept →
inferno8–13-0.0515%27 Sept →
inferno10–13-0.036%27 Sept →
cache13–90.0116%27 Sept →
cache13–90.0115%26 Sept →
mirage9–13-0.0516%26 Sept →
dust213–70.1417%25 Sept →
nuke1–13-0.058%25 Sept →
dust26–130.0017%25 Sept →
office8–13-0.066%25 Sept →
nuke13–40.1024%25 Sept →
vertigo13–20.0816%25 Sept →
mirage6–13-0.014%25 Sept →
anubis3–13-0.086%25 Sept →
anubis13–110.0311%24 Sept →
dust25–13-0.0720%24 Sept →
dust27–130.080%24 Sept →
dust213–70.0511%24 Sept →
mirage8–130.019%24 Sept →
vertigo8–20.040%23 Sept →
nuke2–13-0.0114%23 Sept →
dust213–7-0.0315%23 Sept →
dust213–30.037%22 Sept →
inferno13–20.0116%22 Sept →
dust28–13-0.039%21 Sept →
nuke13–9-0.0011%21 Sept →
inferno13–5-0.025%21 Sept →
cache7–13-0.0518%21 Sept →
dust213–60.0412%21 Sept →
inferno8–8-0.0725%21 Sept →
vertigo12–12-0.088%16 Sept →
dust27–13-0.009%16 Sept →
cache8–13-0.049%16 Sept →
ancient11–130.019%15 Sept →
ancient10–130.018%15 Sept →
dust28–13-0.036%15 Sept →
mirage5–13-0.039%15 Sept →
dust213–9-0.035%14 Sept →
inferno11–130.0710%13 Sept →
dust213–7-0.0310%11 Sept →
dust213–30.1322%11 Sept →
inferno9–13-0.0412%11 Sept →
dust213–80.0522%11 Sept →
mirage4–130.048%11 Sept →
vertigo13–8-0.0019%11 Sept →
train13–60.0312%11 Sept →
nuke13–60.059%11 Sept →
train3–10.1316%11 Sept →
vertigo0–12-0.0346%11 Sept →
nuke7–13-0.0418%11 Sept →
inferno13–9-0.057%10 Sept →
anubis5–13-0.048%10 Sept →
dust28–13-0.009%10 Sept →
inferno13–50.0317%10 Sept →
ancient13–30.0413%10 Sept →
cache7–130.119%9 Sept →
dust213–30.1210%9 Sept →
dust213–50.139%9 Sept →
cache11–130.087%9 Sept →
dust210–130.0512%8 Sept →
dust27–13-0.0516%8 Sept →
nuke16–12-0.058%8 Sept →
shelter13–10-0.027%7 Sept →
office8–13-0.106%7 Sept →
ancient13–50.0520%7 Sept →
inferno9–130.008%6 Sept →
dust27–13-0.039%6 Sept →
dust213–10-0.018%6 Sept →
dust22–13-0.0713%6 Sept →
cache0–13-0.107%6 Sept →
nuke6–130.0111%6 Sept →
ancient6–13-0.085%5 Sept →
dust210–130.0213%5 Sept →
cache13–50.017%5 Sept →
inferno3–13-0.067%5 Sept →
dust213–70.0411%5 Sept →
cache5–13-0.0110%4 Sept →
nuke13–70.0513%4 Sept →
inferno6–13-0.0012%3 Sept →
dust23–13-0.0614%3 Sept →
dust23–13-0.0710%3 Sept →
cache3–13-0.114%3 Sept →
dust26–13-0.058%2 Sept →
ancient9–130.059%2 Sept →
cache9–130.067%2 Sept →
nuke3–13-0.015%2 Sept →
mirage13–50.0711%2 Sept →
office13–11-0.0111%1 Sept →
dust26–13-0.049%1 Sept →
ancient7–13-0.066%1 Sept →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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