The Counter-Strike community has found itself discussing one of the most unusual fan-made analytics projects of the year after a Reddit user published the results of an analysis based on nearly 2,000 professional CS2 demos. What started as a personal data science experiment quickly became one of the most popular discussions on r/GlobalOffensive, generating hundreds of comments and debates about player rankings, team strength, positional impact, and whether advanced statistics can reveal things traditional rankings miss.
A Week of Work and Nearly 2,000 Demos
The author, known as Twisted2kat, spent roughly a week collecting and processing nearly 2,000 professional demos from the past six months. His goal was not to replace HLTV rankings or Valve Regional Standings, but rather to explore whether alternative ranking systems could uncover interesting patterns hidden within professional Counter-Strike data.
It’s a project I worked on for fun, in my free time, and to hopefully learn something along the way.
The project combined team ratings, adjusted player rankings, positional analysis, and player similarity models, creating one of the most ambitious community-driven CS2 analytics projects seen in recent months.
read more
Vitality, ZywOo and makazze Lead the Rankings
One of the first sections focused on team strength. Using an Elo-style system based on the OpenSkill Plackett-Luce model and seeded with Valve Regional Standings data, the author created an alternative ranking system that updated after every match.
The results placed Vitality at the top of the world with a rating of 42.29, ahead of Spirit and NAVI. The biggest surprise came from Legacy and BetBoom, who completed the top five and immediately became a major talking point within the community. Many fans questioned how Falcons could rank below both teams despite their recent success.
The player rankings generated less controversy. ZywOo topped the list with a 1.59 adjusted rating, followed by donk and NAVI’s w0nderful. Ropz and makazze completed the top five.
The appearance of makazze attracted particular attention. While many still associate the Ukrainian talent with academy competition, the analysis suggested he has already been performing at a level comparable to some of the biggest stars in professional Counter-Strike.
Young makazze has actually been frying these past months.
Position Rankings and Surprising Player Comparisons
One of the most interesting parts of the project focused on specific map positions. Instead of only analyzing ratings and kills, the model compared players against others occupying the same roles on each map.
Among the notable findings, makazze, donk, and jabbi ranked among the strongest CT Mid players on Ancient. Mail09, makazze, and Magnojez topped the Anubis B-site rankings, while Senzu, FlameZ, Staehr, and Wicadia emerged as some of the best Banana players on Inferno. The data also suggested that Mirage B anchors average more kills per round than A anchors.
Another section compared players based on role, positioning, AWP usage, and playstyle rather than raw performance. According to the model, the players most similar to ZywOo are r1nkle, molodoy, and s1mple. M0NESY’s closest comparisons were device, w0nderful, and molodoy, while donk’s nearest stylistic matches included xeedo, Magnojez, and NertZ.
These results quickly generated debate, as many fans disagreed with the comparisons while others praised the attempt to analyze player styles through data rather than reputation.
Community Divided Over the Methodology
Despite widespread praise for the effort involved, many users questioned the methodology behind the rankings. Several commenters argued that the numbers were difficult to interpret without detailed explanations of the formulas and validation methods. Others pointed out that a six-month sample size could produce unusual results.
The author later revealed that team ratings came from OpenSkill’s Plackett-Luce model, while the custom round-swing metric relied on thousands of round-state calculations that estimated how much each kill changed a team’s chances of winning a round. He also stated that his results were compared against HLTV’s own round-swing statistics and produced reasonably similar outcomes.
It was never meant to replace VRS or HLTV rankings.
read more
A Growing Interest in CS2 Analytics
Regardless of whether fans agree with every conclusion, the project demonstrates how advanced community-driven Counter-Strike analytics have become. What began as a hobby project quickly turned into one of Reddit’s most discussed CS2 topics and sparked conversations about scouting, player evaluation, and the future of esports statistics.
Many users are already asking the creator to continue collecting data and expand the project over a larger sample size. Whether the rankings prove accurate or not, the discussion itself shows that interest in advanced CS2 analytics continues to grow.
