Is the current HLTV rating flawed? And is there a better alternative on the market?
If you ask some of some renowned faces in the scene, that’s actually the case.
One of the above-mentioned individuals is the former Counter-Strike player and CS:GO analyst Tomi “lurppis” Kovanen, who went on Twitter last night to express his opinion about how Leetify, a CS:GO performance and statistic platform, and its rating is “much better” than HLTV’s.
YNk and Mauisnake chime in
Something the two experts and analysts, Janko “YNk” Paunović and Alex “Mauisnake” Ellenberg back up in two replies on the Tweet.
YNk states that “the fact its economy adjusted makes it instantly better” while Mauisnake calls Leetify’s rating “vastly superior” because of its focus on the economic aspect.
What is Leetify’s rating?
In their own words, it’s a “win rate impact-based and economy-adjusted player rating system”
So, where Leetify believe they differ from other alternatives is that their rating doesn’t value unimpactful kills and kills that are too easy to get that much. You can a lengthy article of Leetify’s rating system here.
A different angle
Towards the end of last year, we spoke with Mohan “launders” Govindasamy, a recognized caster and expert, about this very matter where he took in HLTV in defence, even though agreeing on their rating “is slightly flawed”.
– It’s important that HLTV moves slowly because they are the signature of Counter-Strike online and if they make too many radical changes, and they miss and ratings are far off well then, we’re all screwed, Launders explained and continues:
– It’s clear that HLTV’s rating could be a bit better but I think it’s fine where it is for the moment as long as they are thinking about some changes. Things like eco kills have been a big conversation this year, and I think they are looked at as one-to-on with rifle kills, which I think is incorrect.
Launders also goes more in-depth in the discussion of how to rate players in the interview, which you can find below.
launders: These are the most underrated players of CS:GO
HLTV Rating vs Leetify
HLTV writer and stats connoisseur, Harry ‘NER0’ Richards has taken his time to make a long read where he dives into the differences and contrasts between HLTV’s and Leetify’s. A must-read if you wish to collect as much information about the two rating systems.
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— Harry (@NER0cs) November 15, 2022
Looking at the first chart again, we can see that AWPers and passive players tend to perform better on Leetify than HLTV
Meanwhile aggressive players like Patsi and YEKINDAR are penalised
— Harry (@NER0cs) November 15, 2022
Here we can see that in action
AWPers improve the most in rank, then passive riflers and anchors, with aggressive riflers losing out slightly pic.twitter.com/4EQHuWwZsK
— Harry (@NER0cs) November 15, 2022
On this scatterplot (no rhombus this time, apologies) we can see the yellow dots for this type of player pic.twitter.com/h8WwHFtRQh
— Harry (@NER0cs) November 15, 2022
People like Jame, who have been accused of inflating their HLTV rating thanks to saving, get *even* more reward from Leetify
So, where does this leave us?
— Harry (@NER0cs) November 15, 2022
HLTV show style fairly well with the percentile bars on a player's page
YEKINDAR and Jame have the same rating, but Jame has excellent KAST and DPR while YEKINDAR excels in Impact and ADR pic.twitter.com/9D0mmOzRhC
— Harry (@NER0cs) November 15, 2022
On an eye test we gravitate towards aggressive players. They're flashy, they have that first bullet aim we all love
Yet, defining "aggressive" these days isn't easy.
High opening kill attempts doesn't make someone 2015 apEX — someone else might do the bombsite entry paths
— Harry (@NER0cs) November 15, 2022
And, this is where I see Leetify's approach having value
Players like JDC, and interz entry far more like 2015 apEX than YEKINDAR or Patsi.
And, Leetify's rating gives value to that
— Harry (@NER0cs) November 15, 2022
And that's why we should never, ever, use one metric as the be-all and end-all. Even these great algorithms
Stats are brilliant storytelling tools — but only once you understand their flaws
— Harry (@NER0cs) November 15, 2022
Thread over. Thanks to @leetify for the data ❤️
— Harry (@NER0cs) November 15, 2022
