AI Predicts Which Team Has Most Chance Of Winning The Major


AI Predicts Which Team Has the Highest Chance of Winning PGL Major Stockholm 2021

The team that is most likely to win this Major is.....!!!

Aditya Singh Rawat
Updated On: 
AI predicts which CS:GO team has the maximum chance of winning the PGL Major Stockholm 2021.
Based on the results of over 200,000 simulations, the CS:GO team which has the highest chance of winning the Major is NAVI, with a 30.70%.
The Challengers Stage predictions made by the AI had a success rate of 87.5% while those of the Legends Stage were 62.6%.

The PGL Stockholm Major 2021 has finally reached the Champions Stage with the final eight teams ready to lock horns with each other in a single-elimination bracket. With Ninjas in Pyjamas (NIP) and (VP) already having exited the tournament yesterday following a loss to G2 Esports and Heroic respectively, six teams now remain in contention for the title.

Similar to the previous two stages of the tournament, where an Artificial Intelligence (AI) had predicted which CS:GO teams had the highest chance of qualifying through to the next stage of the Major, another such simulation was run for the Playoffs.

After more than 200,000 simulations being run across the eight team single-elimination bracket, the AI developed by GGPredict calculated which CS:GO team had the highest chance of winning the PGL Major Stockholm 2021.

AI predicts which team has the highest chance of winning the PGL Major Stockholm 2021

A combination of AI and Machine Learning was used to run more than 200,000 simulations for all the eight CS:GO teams that comprise of the PGL Major Stockholm 2021: Champions Stage.

As per the calculations, here are the Major winning chances of all the CS:GO teams that are competing in the Playoffs (Champions Stage):

  1. Natus Vicnere - 30.70%

  2. Heroic - 14.87%%

  3. G2 Esports - 13.24%

  4. Team Vitality - 9.35%

  5. Gambit Esports - 9.28%

  6. FURIA Esports - 7.83%

  7. - 7.54%

  8. Ninjas in Pyjamas - 7.19%

After the results of the first day of the Champions Stage, it is safe to say that so far the AI calculations have been on point. This is because both the teams predicted to have the lowest chance of winning the Stockholm Major, VP and NIP, have been eliminated from the tournament.

The previous simulations run by the AI have also shown a high success rate.

  • Five out of their eight predictions were right following the Legends Stage simulation, which is a success rate of 62.6%.

  • Seven out of their eight predictions were right following the Challengers Stage simulations, which is a success rate of 87.5%.

  • In totality, the simulations have accurately predicted 12 out of 16 picks, which is a success rate of 75%.

This is a pretty good success rate considering the number of right Pick'Em predictions it would results in for the Stockholm 2021 Viewer Pass users.

PGL Major New Champions Stage - Complete Predictions

As per GGPredict, who have conducted all the simulations and come up with the predictions listed above, the system in place does not account for which map is being played or where the match is taking place (LAN/online). However, it still takes into consideration the statistics of all the players on the team, recent performances of all the teams, strength of their opponents, and the tournament level.

There are drawbacks to this system of prediction such as, the recent results of all the teams are given more weightage, the human element of how well a team or an individual handles stress is not taken into consideration, and teams that mostly compete in a closed region could result in a skewed outcome as their local competitors are considered significantly weaker.

As per GGpredict, the simulations and data represented by them is mostly for fun and the real outcome may vary significantly.

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Aditya is the in-house CS:GO writer at AFK Gaming. While his understanding of the esports space is not restricted by geographical borders, his current focus lies in the Asian region. Understands and follows almost all major esport titles.