RLCS Predictions

Regionals Predictions

Regionals Probabilities
TEAM Make Quarters Make Semis Make Final Win Final
Spacestation Gaming 61% 36%
G2 Esports 60% 29%
Susquehanna Soniqs 61% 20% 7%
NRG Esports 79% 33% 15%
Cloud9 62% 41% 18% 10%
Ghost Gaming 38% 20% 7% 3%
NA
Regionals Probabilities
TEAM Make Quarters Make Semis Make Final Win Final
Renault Vitality 60% 35%
Dignitas 50% 22%
Team Reciprocity 77% 37% 17%
mousesports 77% 36% 17%
Veloce Esports 46% 21% 8% 4%
FC Barcelona 54% 25% 10% 4%
EU
Based on 5,000 simulations.
Click here to view previous week's regional predictions.

Match Predictions

Previous Weeks

Week 8
AS Monaco 39% 61% Team Singularity
mousesports 61% 39% Endpoint
FC Barcelona 71% 29% Team SoloMid
Team Reciprocity 49% 51% Dignitas
FC Barcelona 50% 50% mousesports
Renault Vitality 63% 37% Veloce Esports
EU
Week 8
NRG Esports 55% 45% Ghost Gaming
Spacestation Gaming 80% 20% eUnited
Pittsburgh Knights 32% 68% Cloud9
Spacestation Gaming 52% 48% G2 Esports
Rogue 50% 50% Flight
G2 Esports 59% 41% Susquehanna Soniqs
NA
Week 7
Dignitas 62% 38% Endpoint
Team Reciprocity 72% 28% Team SoloMid
Team Singularity 39% 61% Endpoint
Veloce Esports 51% 49% Dignitas
FC Barcelona 75% 25% AS Monaco
Renault Vitality 61% 39% mousesports
EU
Week 7
(Team Fireburner) Cloud9 40% 60% Susquehanna Soniqs
Spacestation Gaming 73% 27% Rogue
Flight 33% 67% Susquehanna Soniqs
Ghost Gaming 69% 31% Cloud9
Pittsburgh Knights 52% 48% eUnited
NRG Esports 43% 57% G2 Esports
NA
Week 6
FC Barcelona 69% 31% Team Singularity
Team SoloMid 50% 50% Endpoint
Veloce Esports 60% 40% mousesports
Team Reciprocity 76% 24% AS Monaco
Renault Vitality 59% 41% Dignitas
EU
Week 6
Spacestation Gaming 72% 28% Flight
eUnited 44% 56% Susquehanna Soniqs
Ghost Gaming 44% 56% G2 Esports
Pittsburgh Knights 56% 44% Rogue
NRG Esports 78% 22% Cloud9
NA
Week 5
Team SoloMid 66% 34% Team Singularity
Veloce Esports 82% 18% AS Monaco
Team Reciprocity 70% 30% Endpoint
Team SoloMid 40% 60% mousesports
FC Barcelona 46% 54% Dignitas
Renault Vitality 61% 39% Team Reciprocity
EU
Week 5
eUnited 71% 29% Flight
Ghost Gaming 75% 25% Rogue
Pittsburgh Knights 48% 52% Susquehanna Soniqs
eUnited 20% 80% G2 Esports
Spacestation Gaming 72% 28% Cloud9
NRG Esports 72% 28% Pittsburgh Knights
NA
Week 4
Veloce Esports 76% 24% Team Singularity
Renault Vitality 81% 19% AS Monaco
Veloce Esports 71% 29% Endpoint
Team Reciprocity 62% 38% FC Barcelona
Team SoloMid 55% 45% AS Monaco
Dignitas 66% 34% mousesports
EU
Week 4
Ghost Gaming 70% 30% Flight
NRG Esports 70% 30% Rogue
Ghost Gaming 52% 48% Susquehanna Soniqs
eUnited 42% 58% Rogue
Pittsburgh Knights 35% 65% Spacestation Gaming
Cloud9 23% 77% G2 Esports
NA
Week 3
Dignitas 85% 15% Team Singularity
AS Monaco 51% 49% Endpoint
mousesports 68% 32% Team Singularity
Renault Vitality 73% 27% Team SoloMid
Team Reciprocity 66% 34% Veloce Esports
Renault Vitality 44% 56% FC Barcelona
EU
Week 3
Cloud9 36% 64% Flight
Rogue 49% 51% Susquehanna Soniqs
G2 Esports 86% 14% Flight
NRG Esports 80% 20% eUnited
Pittsburgh Knights 31% 69% Ghost Gaming
NRG Esports 71% 29% Spacestation Gaming
NA
Description

The forecasts above are based on 1,000 simulations for each game. I use Markov chain to simulate the events of each team and their opponent. Events could include shots, saves, passes, etc. I house the transition probabilities in a transition matrix. A transition probability is defined as the probability of an event occurring given a certain event has just occurred. For example, one transition probability would be the probability of team B saving the ball when team A shoots the ball. Transition matrices are constructed using play-by-play data from previous weeks. The model is rather simplistic and does not take into account things like momentum (which is an important factor to consider in Rocket League). Future work will take this into account as well as explore how similar certain teams are with the hope of increasing the accuracy of my forecasts. Predictions should become more accurate as the season goes on, thus we should get a more accurate picture of how teams behave. Future work will also include using priors to forecast games when there is little data about one or both of the teams. I also plan on evaluating my predictions in order to calibrate or even rework my model.

Lastly, I plan on ranking each team from NA and EU, giving them an SPI score, and offensive score, and a defensive score. I am not sure when I will get to all of this (as I am currently working and finishing up grad school) so don't hold your breath. Thanks for visiting!

Clich here to see how this model performs.