All posts by Sam Walczak

Game Predictions | March Madness 2022

The table below provides our predictions for all games in the 2022 NCAA Tournament. The table will be updated after each round of the tournament, with new games/predictions added as they become available. A brief description of how to interpret the predictions is provided above the table, and a summary of the historical accuracy of each model is provided at the end of the post. See our related posts on our Full 2022 Tournament Bracket and our Tournament Simulation results.
Continue reading Game Predictions | March Madness 2022

Model 284 Bracket | March Madness 2022

Below is our Model 284 consensus bracket for the 2022 NCAA Tournament. As you will see from our Game-by-Game Predictions and Tournament Simulation results, our bracket does not necessarily advance our model’s predicted winner for every single game. Rather, we use a combination of (1) our model’s individual game predictions, (2) our tournament simulation results, (3) injuries / other factors not captured by our models, and (4) consideration of public picks – to make sure we are differentiating our bracket enough from the most popular choices. For those interested, here is a bracket filled out purely using raw model output. Continue reading Model 284 Bracket | March Madness 2022

Tournament Simulation | March Madness 2022

The article below shows how our models view this year’s tournament field from a simulation perspective. Each table shows the % chance that each team advances to a given round of the tournament (e.g., in the first table, Gonzaga has a 92.5% chance of advancing to the 2nd round). These figures are calculated based on 5,000 simulations of this year’s tournament, which were performed using win probability and spread predictions from our models. See our related posts for our Full 2022 Tournament Bracket and our Game-by-Game Predictions. Continue reading Tournament Simulation | March Madness 2022

Game Predictions | March Madness 2021

The table below provides our predictions for all games in the 2021 NCAA Tournament. The table will be updated after each round of the tournament, with new games/predictions added as they become available. A brief description of how to interpret the predictions is provided above the table, and a summary of the historical accuracy of each model is provided at the end of the post. See our related posts on our Full 2021 Tournament Bracket and our Tournament Simulation results.
Continue reading Game Predictions | March Madness 2021

Model 284 Bracket | March Madness 2021

Below is our Model 284 consensus bracket for the 2021 NCAA Tournament. As you will see from our Game-by-Game Predictions and Tournament Simulation results, our bracket does not necessarily advance our model’s predicted winner for every single game. Rather, we use a combination of (1) our model’s individual game predictions, (2) our tournament simulation results, (3) injuries / other factors not captured by our models, and (4) consideration of public picks – to make sure we are differentiating our bracket enough from the most popular choices. For those interested, here is a bracket filled out purely using raw model output. Continue reading Model 284 Bracket | March Madness 2021

Tournament Simulation | March Madness 2021

The article below shows how our models view this year’s tournament field from a simulation perspective. Each table shows the % chance that each team advances to a given round of the tournament (e.g., in the first table, Gonzaga has a 92.5% chance of advancing to the 2nd round). These figures are calculated based on 1,000 simulations of this year’s tournament, which were performed using win probability and spread predictions from our models. See our related posts for our Full 2021 Tournament Bracket and our Game-by-Game Predictions. Continue reading Tournament Simulation | March Madness 2021

2021 NFL Big Data Bowl Submission

A Framework for Accessing Individual Defensive Performance in Coverage

1. Introduction

Current defensive coverage metrics are only calculated on plays where that defender’s assigned offensive player is the one targeted. This approach is flawed and incomplete. On any given play, there are around five available receivers, and the best coverage may prevent the quarterback from even throwing the ball to a given receiver. Further, these metrics identify coverage assignment simply by considering the responsible defender to be the nearest one at the time the ball arrives. Thus, this methodology only gives us coverage assignment for one player per play, and even that assignment is questionable; the closest defender at one particular moment isn’t necessarily the assigned defender.

The work presented here illustrates a framework we’ve developed to address these shortcomings. Our approach begins by identifying the responsibilities of each defender on a given play. If a player is in man (everywhere) coverage, he is assigned a specific offensive player whom he is to cover until the ball is thrown. On the other hand, if a player is in zone coverage, he is instead responsible for an area and any receivers who enter that area. Because the responsibilities of a player differ in each coverage type, the evaluation of performance should be different for each. Once we identify the type of coverage being played by each defender, we then consider two separate time points for evaluation. For one, we consider the time frame after the pass is thrown. This is the most straightforward but limits us to only the targeted receivers, as players tend to abandon their assignments and converge to the ball once it is thrown. To include all defenders in our analysis, we also consider the time frame between the snap and the pass. Figure 1 below illustrates our proposed framework…….

Read our full paper on Kagge here: https://www.kaggle.com/model284/a-defensive-player-coverage-evaluation-framework

Game Predictions | March Madness 2019

The tables below provide our predictions for all games in the 2019 NCAA Tournament. The tables will be updated after each round of the tournament, with new games/predictions added as they become available. A brief description of how to interpret the predictions is provided above each table, and a summary of the historical accuracy of each model is provided at the end of the post.
Continue reading Game Predictions | March Madness 2019