Pellervo

Pellervo — CS2 Stats

FI76561199026012383[U:1:1065746655]Steam profile ↗✓ No bans

238Tracked matches43%Win rate2022Tracked since
CSDB Rating2.8 LearningPositional Player
WingmanSilver IV
Ladder ranks via Leetify

Rating over time

5,501Peak Premier in tracked matches
38Days played since 2026-02-27

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

Performance scores

Aim44
Positioning38
Utility13

0–100 skill scores via Leetify.

Recent form

COLD49–44–7Last 10049%Win rateLLLLLLWWLT

Last 10 vs previous 10: −40pp win rate · −0.05 avg rating · −0.7pp headshot accuracy · +25ms reaction

Win rate down 40pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 0–5 · 0% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 13%
  • Avg reaction 516ms

Last 10

  • 2–7–1 · 20% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 15%
  • Avg reaction 603ms

Last 20

  • 8–10–2 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 15%
  • Avg reaction 591ms

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 (+2.1 against its own average).

Aim4.4
Utility1.3
Positioning3.8
Opening Duels0.0

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

iM

Plays most like iM 91% 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. 580ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 60% 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

Aim4.4
Positioning3.8
Utility1.3
Mechanics2.1
Opening Duels0.0
Win Impact2.6

Composite 2.8/10 (Learning), 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

Match rating-0.03+0.01
first ⅓ avg -0.04 → last ⅓ avg -0.03
Reaction time582ms−63ms
first ⅓ avg 645ms → last ⅓ avg 582ms
Headshot accuracy13.7%+0.8%
first ⅓ avg 12.9% → last ⅓ avg 13.7%

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

0.11Best match rating · 4–3 · inferno, 18 Mar →
40%Best headshot accuracy · 13–7 · office, 20 Apr →
391msFastest reaction time · 2–13 · office, 17 Apr →
13–1Biggest win · office, 15 Aug →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L6Current streak
10–3In matches decided by ≤2 rounds
2Overtime games

Map breakdown

nukeBest map · 65% over 17cacheWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
nukeS1711–665%-0.00
infernoC146–843%-0.02
mirageB137–654%-0.05
dust2A138–562%-0.03
officeB115–645%-0.01
ancientA106–460%-0.02
cacheD72–529%-0.05
overpassC52–340%-0.07
vertigo—41–325%-0.03
anubis—41–325%-0.06
train—20–20%-0.11

Across the last 100 tracked matches.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

14.4%Headshot accuracy
32.0%Accuracy (enemy spotted)
34.1%Spray accuracy
59.7%Counter-strafing
9.5°Preaim
580msReaction time
18.6%T opening success
30.4%CT opening success
0.16Enemies flashed / flash
0.0%Flash assists
8.82HE damage / grenade
1.42Flashes / 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 14.3719% — below the 15% mark we flag

    Aim Training →
  2. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.1642 — below the 0.5 mark we flag

    Grenade Lineups →
  3. 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 18.5739% — below the 40% mark we flag

Spend your practice time on Cache

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 7 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
mirage6–13-0.104%23 Oct →
dust21–6-0.0514%11 Sept →
office5–13-0.087%11 Sept →
vertigo11–13-0.0417%5 Sept →
inferno5–13-0.0924%5 Sept →
overpass3–13-0.0913%5 Sept →
dust213–4-0.0029%5 Sept →
nuke13–50.0115%5 Sept →
ancient7–13-0.1015%5 Sept →
mirage12–12-0.0112%5 Sept →
cache12–12-0.0810%5 Sept →
office13–9-0.0815%27 Aug →
nuke7–130.0314%20 Aug →
inferno6–130.025%20 Aug →
nuke13–9-0.063%20 Aug →
cache13–4-0.0222%16 Aug →
dust213–40.0538%16 Aug →
nuke16–120.0519%16 Aug →
mirage16–14-0.0418%16 Aug →
office5–130.0814%16 Aug →
nuke13–4-0.0214%15 Aug →
mirage13–6-0.0214%15 Aug →
office13–1-0.0417%15 Aug →
office10–13-0.0111%14 Aug →
vertigo8–130.058%4 Jul →
office5–13-0.079%4 Jul →
overpass1–9-0.115%18 Jun →
ancient13–30.0614%17 Jun →
inferno6–13-0.0310%17 Jun →
dust22–13-0.1025%17 Jun →
nuke9–70.0113%17 Jun →
inferno8–8-0.056%17 Jun →
inferno2–8-0.100%29 May →
office0–13-0.0525%29 May →
cache8–13-0.0912%20 May →
dust213–10-0.0111%18 May →
cache4–13-0.1015%8 May →
nuke9–70.0015%8 May →
cache13–6-0.010%7 May →
nuke9–50.0219%5 May →
cache10–13-0.050%30 Apr →
cache7–13-0.0313%29 Apr →
mirage13–1-0.044%24 Apr →
office13–9-0.0013%24 Apr →
mirage9–130.0016%23 Apr →
ancient13–10.098%23 Apr →
office13–30.0916%23 Apr →
nuke7–12-0.0211%22 Apr →
overpass13–11-0.0414%22 Apr →
dust213–9-0.0021%22 Apr →
vertigo10–13-0.0517%20 Apr →
dust213–8-0.0215%20 Apr →
ancient13–5-0.0410%20 Apr →
overpass11–13-0.0113%20 Apr →
inferno2–6-0.0515%20 Apr →
nuke3–13-0.0212%20 Apr →
dust210–13-0.0223%20 Apr →
anubis13–9-0.0320%20 Apr →
mirage2–00.000%20 Apr →
office13–70.0640%20 Apr →
mirage12–12-0.0814%17 Apr →
nuke13–30.0713%17 Apr →
inferno13–4-0.0211%17 Apr →
dust28–00.006%17 Apr →
ancient13–11-0.0420%17 Apr →
office2–13-0.039%17 Apr →
mirage12–12-0.106%16 Apr →
vertigo13–9-0.0811%16 Apr →
nuke13–10-0.0112%16 Apr →
mirage13–5-0.0810%7 Apr →
ancient2–13-0.0519%2 Apr →
nuke13–9-0.0310%2 Apr →
mirage13–7-0.0218%2 Apr →
ancient13–7-0.0110%2 Apr →
mirage3–12-0.055%1 Apr →
inferno13–9-0.0410%1 Apr →
dust213–6-0.039%1 Apr →
anubis10–13-0.0414%1 Apr →
mirage13–11-0.0810%31 Mar →
ancient11–13-0.0912%30 Mar →
inferno13–8-0.0110%27 Mar →
overpass13–11-0.1113%27 Mar →
nuke8–13-0.0112%27 Mar →
inferno13–70.0728%23 Mar →
nuke13–8-0.059%23 Mar →
dust213–5-0.028%23 Mar →
inferno7–13-0.0415%21 Mar →
ancient9–13-0.059%21 Mar →
anubis5–13-0.1018%19 Mar →
ancient13–110.0214%19 Mar →
dust210–13-0.0912%18 Mar →
inferno13–100.0111%18 Mar →
nuke4–130.0214%18 Mar →
inferno4–30.1136%18 Mar →
train12–12-0.1214%17 Mar →
dust21–13-0.1113%13 Mar →
inferno5–13-0.0510%13 Mar →
nuke12–12-0.0210%13 Mar →
train4–13-0.118%27 Feb →
anubis7–13-0.0811%27 Feb →

Match data via Leetify.

Recent teammates

Milestones

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

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