If the regular season serves as an indicator for what we will see in the playofss, we are certainly in for a treat! With the playoffs for the Basketball Champions League right around the corner, we make our predictions – that will keep being updated as the playoffs progress. First we start with the final… Read More Basketball Champions League Predictions: Playoffs 2017-18
Evaluating lineups has traditionally been one of the tasks that “analytics” are commissioned with in basketball (and other sports with frequent substitutions). 5, 3 and 2 men lineups are typically analyzed, with the latter two offering a larger sample to work with. The metric that is typically utilized to evaluate the performance of a lineup… Read More Basketball Lineup Ratings: a Bayesian Adjustment Approach
Happy New Year! And happy new NFL season, that is, the NFL playoffs! The 12 teams that made it this year are already known and this upcoming weekend the wild card games are happening. Our predictions are based on 100,000 simulations of the tournament with the win probabilities obtained from the football prediction matchup algorithm… Read More January Football is Back: NFL playoff predictions
Shooting charts have been an integral part of a basketball game’s summary for quiet some time now. Fans like visual information and can easily grasp it. However, if one wants to understand the shooting patterns of teams/players and how they differ (and how potentially this can drive pre-game scouting and in-game strategy) heuristic comparison of… Read More A Shooting Dictionary for Players and Teams in Basketball Champions League
A recent article described how the volume of three-point shots taken in the Basketball Champions League (BCL) has shown an increasing trend – in alignment with the trend in the NBA that has been observed for several years now and has coincided with the ascent of the analytics movement in the sport. The analytical explanation of… Read More Offensive and Defensive Efficiency in Basketball Champions League
Many times, in sports we need to evaluate players with limited information. Should we sign a QB for whom we have only observed 30 pass attempts? What is our best estimate for the probability distribution for his yards/attempt? What about a kicker that has only taken 5 field goals of 50+ yards? How can we decide… Read More Bayesian player evaluation
With the NHL season right around the corner, this marks my first ever post on hockey. Clearly hockey is not my sport, but this shows how math and analytics can cast a net over all sports. One of the constant questions in sports is how much of a team’s or player’s success is due to… Read More Faceoffs: Skill or Luck?