nfelo: a power ranking, prediction, and betting model for the NFL

Related tags

Deep Learningnfelo
Overview

nfelo

nfelo is a power ranking, prediction, and betting model for the NFL. Nfelo take's 538's Elo framework and further adapts it for the NFL, hence the name nfelo (pronounced "NFL oh").

The model's output is visualized on nfeloapp.com where you can explore:

Repository Description

This repository contains all the code necessary to translate raw data into weekly predictions. This process has three main phases:

  1. Pull and scrape data from nflfastR, PFF, and various Vegas Line sites
  2. Compile data into a single dataset and run intermediate models (nfelo ratings and wepa)
  3. Translate power ratings and contextual game information into win and line expectations

Install and Use

nfelo is a python package. To install, simply download this repository into your site-packages folder and install the dependencies detailed in the requirements.txt file.

Because nfelo pulls from PFF, running the model requires you to access team grades that are behind a paywall (sorry!), and the PFF scraper does require you to copy your cookie into the config_private.json file. This cookie must be refreshed before each run.

Each phase of the build can be run individually, but to generate predictions, run the following script:

import nfelo

## update data ##
nfelo.pull_nflfastR_pbp()
nfelo.pull_nflfastR_game()
nfelo.pull_nflfastR_roster()
nfelo.pull_nflfastR_logo()
nfelo.pull_538_games()
nfelo.pull_sbr_lines()
nfelo.pull_tfl_lines()
nfelo.pull_pff_grades()

## format ##
nfelo.format_spreads()
nfelo.game_data_merge()

## update models ##
nfelo.calculate_wepa()
nfelo.calculate_nfelo()

## ouput spreads ##
nfelo.calculate_spreads()

This process will output a csv in the output_data folder called 'predictions.csv'

Because this package is exclusively used as a workflow automation for building nfelo predictions each week, it's not well suited for other uses and likely has some bugs if updates are run before every game for a given week has been completed. It does produce nfelo rankings, wepa results, and a few other datapoints, which can be found in various csvs within the folder hierarchy.

Authors

This package is built and maintained by @greerreNFL. Feel free to DM with comments and questions.

Version History

  • 0.1
    • Initial package release
    • Includes nfelo v3.0 and workflow automations to recreate weekly predictions
Pretrained Pytorch face detection (MTCNN) and recognition (InceptionResnet) models

Face Recognition Using Pytorch Python 3.7 3.6 3.5 Status This is a repository for Inception Resnet (V1) models in pytorch, pretrained on VGGFace2 and

Tim Esler 3.3k Jan 04, 2023
Hypernetwork-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels

Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels The implementation of Hypernet-Ensemble Le

Sungmin Hong 6 Jul 18, 2022
UFPR-ADMR-v2 Dataset

UFPR-ADMR-v2 Dataset The UFPR-ADMRv2 dataset contains 5,000 dial meter images obtained on-site by employees of the Energy Company of Paraná (Copel), w

Gabriel Salomon 8 Sep 29, 2022
A Robust Non-IoU Alternative to Non-Maxima Suppression in Object Detection

Confluence: A Robust Non-IoU Alternative to Non-Maxima Suppression in Object Detection 1. 介绍 用以替代 NMS,在所有 bbox 中挑选出最优的集合。 NMS 仅考虑了 bbox 的得分,然后根据 IOU 来

44 Sep 15, 2022
Latent Execution for Neural Program Synthesis

Latent Execution for Neural Program Synthesis This repo provides the code to replicate the experiments in the paper Xinyun Chen, Dawn Song, Yuandong T

Xinyun Chen 16 Oct 02, 2022
Code samples for my book "Neural Networks and Deep Learning"

Code samples for "Neural Networks and Deep Learning" This repository contains code samples for my book on "Neural Networks and Deep Learning". The cod

Michael Nielsen 13.9k Dec 26, 2022
patchmatch和patchmatchstereo算法的python实现

patchmatch patchmatch以及patchmatchstereo算法的python版实现 patchmatch参考 github patchmatchstereo参考李迎松博士的c++版代码 由于patchmatchstereo没有做任何优化,并且是python的代码,主要是方便解析算

Sanders Bao 11 Dec 02, 2022
MAg: a simple learning-based patient-level aggregation method for detecting microsatellite instability from whole-slide images

MAg Paper Abstract File structure Dataset prepare Data description How to use MAg? Why not try the MAg_lib! Trained models Experiment and results Some

Calvin Pang 3 Apr 08, 2022
Degree-Quant: Quantization-Aware Training for Graph Neural Networks.

Degree-Quant This repo provides a clean re-implementation of the code associated with the paper Degree-Quant: Quantization-Aware Training for Graph Ne

35 Oct 07, 2022
Qt-GUI implementation of the YOLOv5 algorithm (ver.6 and ver.5)

YOLOv5-GUI 🎉 YOLOv5算法(ver.6及ver.5)的Qt-GUI实现 🎉 Qt-GUI implementation of the YOLOv5 algorithm (ver.6 and ver.5). 基于YOLOv5的v5版本和v6版本及Javacr大佬的UI逻辑进行编写

EricFang 12 Dec 28, 2022
School of Artificial Intelligence at the Nanjing University (NJU)School of Artificial Intelligence at the Nanjing University (NJU)

F-Principle This is an exercise problem of the digital signal processing (DSP) course at School of Artificial Intelligence at the Nanjing University (

Thyrix 5 Nov 23, 2022
Scheme for training and applying a label propagation framework

Factorisation-based Image Labelling Overview This is a scheme for training and applying the factorisation-based image labelling (FIL) framework. Some

Wellcome Centre for Human Neuroimaging 2 Dec 17, 2021
Automated detection of anomalous exoplanet transits in light curve data.

Automatically detecting anomalous exoplanet transits This repository contains the source code for the paper "Automatically detecting anomalous exoplan

1 Feb 01, 2022
Anomaly Detection Based on Hierarchical Clustering of Mobile Robot Data

We proposed a new approach to detect anomalies of mobile robot data. We investigate each data seperately with two clustering method hierarchical and k-means. There are two sub-method that we used for

Zekeriyya Demirci 1 Jan 09, 2022
Implementation of fast algorithms for Maximum Spanning Tree (MST) parsing that includes fast ArcMax+Reweighting+Tarjan algorithm for single-root dependency parsing.

Fast MST Algorithm Implementation of fast algorithms for (Maximum Spanning Tree) MST parsing that includes fast ArcMax+Reweighting+Tarjan algorithm fo

Miloš Stanojević 11 Oct 14, 2022
A project for developing transformer-based models for clinical relation extraction

Clinical Relation Extration with Transformers Aim This package is developed for researchers easily to use state-of-the-art transformers models for ext

uf-hobi-informatics-lab 101 Dec 19, 2022
Pytorch implementation of FlowNet by Dosovitskiy et al.

FlowNetPytorch Pytorch implementation of FlowNet by Dosovitskiy et al. This repository is a torch implementation of FlowNet, by Alexey Dosovitskiy et

Clément Pinard 762 Jan 02, 2023
An example showing how to use jax to train resnet50 on multi-node multi-GPU

jax-multi-gpu-resnet50-example This repo shows how to use jax for multi-node multi-GPU training. The example is adapted from the resnet50 example in d

Yangzihao Wang 20 Jul 04, 2022
Codebase for Amodal Segmentation through Out-of-Task andOut-of-Distribution Generalization with a Bayesian Model

Codebase for Amodal Segmentation through Out-of-Task andOut-of-Distribution Generalization with a Bayesian Model

Yihong Sun 12 Nov 15, 2022
【ACMMM 2021】DSANet: Dynamic Segment Aggregation Network for Video-Level Representation Learning

DSANet: Dynamic Segment Aggregation Network for Video-Level Representation Learning (ACMMM 2021) Overview We release the code of the DSANet (Dynamic S

Wenhao Wu 46 Dec 27, 2022