Filip Thorvaldsen

Filip Thorvaldsen — CS2 Stats

YE76561198872227064[U:1:911961336]Steam profile ↗✓ No bans

109Tracked matches54%Win rate2021Tracked since
CSDB Rating7.7 StrongOpening Duellist
Ladder ranks via Leetify

Performance scores

Aim85
Positioning86
Utility54

0–100 skill scores via Leetify.

Recent form

HOT66–25–9Last 10066%Win rateWWLWWWLLWW

Last 10 vs previous 10: 0pp win rate · +0.01 avg rating · +4.2pp headshot accuracy · −58ms reaction

Win rate 0pp 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

  • 4–1 · 80% win rate
  • Avg rating 0.08
  • Avg headshot accuracy 30%
  • Avg reaction 495ms

Last 10

  • 7–3 · 70% win rate
  • Avg rating 0.08
  • Avg headshot accuracy 28%
  • Avg reaction 535ms

Last 20

  • 14–6 · 70% win rate
  • Avg rating 0.08
  • Avg headshot accuracy 26%
  • Avg reaction 564ms

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: Opening Duellist — Winning opening duels is what stands out in this profile (+1.5 against its own average). How often you WIN the first duel — CSDB cannot yet see how often you take it.

Aim8.5
Utility5.4
Positioning8.6
Opening Duels9.3

Sharp aimerStrong positioning

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

s1mple

Plays most like s1mple 78% playstyle similarity

Most alike: positioning profile, opening-duel success.

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

CT openings. 66% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

T openings. 65% T opening-duel success — entries that actually open the round.

Areas to improve

Preaim. Mechanical aim is strong but the crosshair sits 10.1° off target when enemies appear — placement, not flicking, is the bigger win available.

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 568ms 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

Aim8.5
Positioning8.6
Utility5.4
Mechanics7.1
Opening Duels8.9
Win Impact6.2

Composite 7.7/10 (Strong), 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 rating0.06−0.04
first ⅓ avg 0.10 → last ⅓ avg 0.06
Reaction time562ms−3ms
first ⅓ avg 566ms → last ⅓ avg 562ms
Headshot accuracy27.7%+4.0%
first ⅓ avg 23.6% → last ⅓ avg 27.7%

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

0.30Best match rating · 9–5 · mirage, 18 Aug →
100%Best headshot accuracy · 0–2 · nuke, 3 Jan →
383msFastest reaction time · 13–1 · office, 1 Oct →
16–1Biggest win · anubis, 14 Jan →

Across the last 100 tracked matches.

Highlights

8Longest win streak
W2Current streak
3–4In matches decided by ≤2 rounds
11Overtime games

Map breakdown

overpassBest map · 83% over 6infernoWeakest map · 40% over 10
MapGradePlayedRecordWin rateAvg rating
mirageB2111–1052%0.09
nukeS1612–475%0.08
infernoC104–640%0.06
anubisS107–370%0.07
ancientS75–271%0.07
vertigoA74–357%0.09
dust2S75–271%0.07
overpassS65–183%0.07
trainB63–350%0.04
jura—33–0100%0.08
office—22–0100%0.12
grail—22–0100%0.11
stronghold—11–0100%0.14
alpine—11–0100%0.10
palacio—11–0100%0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (40% over 10). 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.

25.6%Headshot accuracy
36.8%Accuracy (enemy spotted)
41.0%Spray accuracy
82.0%Counter-strafing
10.1°Preaim
568msReaction time
65.1%T opening success
66.0%CT opening success
0.45Enemies flashed / flash
9.3%Flash assists
9.56HE damage / grenade
8.65Flashes / 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. 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 0.4512 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Inferno

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

40% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno13–40.0329%26 Mar →
nuke13–80.1225%26 Mar →
anubis3–130.0423%23 Feb →
inferno13–80.0833%23 Feb →
nuke10–30.1040%23 Feb →
nuke13–110.0835%20 Feb →
inferno11–130.0725%19 Feb →
nuke9–130.0815%19 Feb →
stronghold13–90.1433%25 Jan →
alpine13–110.1023%25 Jan →
anubis13–90.1340%20 Jan →
overpass13–60.1125%20 Jan →
mirage1–8-0.070%19 Jan →
train13–100.0530%19 Jan →
inferno6–130.0723%18 Jan →
mirage3–130.1235%18 Jan →
nuke13–50.1021%16 Jan →
nuke13–90.0921%16 Jan →
overpass13–100.0921%16 Jan →
nuke13–30.0523%16 Jan →
ancient12–120.0616%15 Jan →
anubis12–120.0825%15 Jan →
mirage2–90.0734%3 Jan →
inferno5–13-0.0012%3 Jan →
mirage13–160.0824%3 Jan →
nuke0–2-0.01100%3 Jan →
train6–130.0519%3 Jan →
mirage9–130.0628%23 Dec →
vertigo13–50.1029%23 Dec →
inferno9–130.0420%21 Nov →
nuke13–80.0225%20 Nov →
inferno13–9-0.0528%12 Nov →
nuke15–150.0232%11 Nov →
train12–120.0816%11 Nov →
mirage10–130.0122%9 Nov →
mirage13–100.0540%2 Nov →
inferno13–20.1737%2 Nov →
overpass13–30.0747%2 Nov →
mirage0–3-0.020%25 Oct →
dust213–40.0521%25 Oct →
train13–60.0924%24 Oct →
dust213–3-0.0016%24 Oct →
mirage13–80.1238%10 Oct →
palacio13–60.0514%5 Oct →
jura13–80.1635%1 Oct →
office13–10.1529%1 Oct →
office7–20.1038%1 Oct →
inferno12–120.0625%11 Aug →
nuke5–130.1038%11 Aug →
mirage12–120.0925%11 Aug →
anubis13–5-0.0354%29 Jul →
mirage13–80.1633%29 Jul →
ancient13–00.1722%29 Jul →
ancient13–30.0728%26 Jul →
ancient13–70.1027%25 Jul →
vertigo13–60.2332%25 Jul →
nuke13–100.0335%11 Jul →
overpass13–70.1232%11 Jul →
vertigo11–130.0222%11 Jul →
dust24–13-0.0022%4 Jul →
anubis13–7-0.0233%4 Jul →
mirage13–90.1325%4 Jul →
ancient13–9-0.0316%4 Jul →
dust27–13-0.0320%4 Jul →
mirage1–6-0.0238%1 Jul →
jura13–30.0523%1 Jul →
vertigo6–20.0144%1 Jul →
train13–90.0625%27 Jun →
dust213–20.0923%27 Jun →
overpass12–12-0.0425%25 Jun →
nuke8–00.1822%25 Jun →
anubis13–10.1120%25 Jun →
mirage13–70.0423%25 Jun →
anubis13–100.0218%24 Jun →
train3–13-0.0938%24 Jun →
mirage0–20.06100%23 Jun →
grail13–20.1010%22 Jun →
mirage13–80.0112%22 Jun →
anubis12–120.0113%22 Jun →
mirage13–10.1632%22 Jun →
nuke13–100.1227%21 Jun →
jura13–20.0320%21 Jun →
vertigo7–130.0632%21 Jun →
grail13–30.1128%20 Jun →
nuke16–130.0312%28 Jul →
anubis16–10.1622%14 Jan →
dust27–10.2621%6 Oct →
mirage10–10.1910%6 Oct →
overpass16–90.0619%6 Oct →
ancient10–160.0625%30 Sept →
mirage9–50.0429%23 Sept →
mirage9–10.2718%23 Sept →
nuke9–40.1424%23 Sept →
vertigo16–110.1319%7 Sept →
mirage9–50.3021%18 Aug →
anubis9–30.2326%17 Aug →
vertigo13–160.1012%24 Jun →
inferno15–150.1017%7 Jan →
ancient16–140.0723%9 Dec →
dust216–100.1316%9 Dec →

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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