Tutorial: Web Scraping

Our first tutorial is coming up on Friday, October 23rd at 7:00pm EST. We’ll be providing an introduction to web scraping with Python.
Zoom Link: https://utoronto.zoom.us/j/3813974797 (Passcode: 095799)

Learn how to web scrape
Web Scraping is a valuable tool, especially for those that enjoy creating independent coding projects. It allows for more creative projects by giving the user the ability to obtain their own niche data. This tutorial will focus on the fundamentals of how to web scrape, with additional focus on how a webpage is broken down and how to clean your obtained data.

We hope to see you there!

Upcoming Seminars

Here is a list of the upcoming seminars we’ll be hosting. Full details are also sent via our email newsletter. All times are in EST.

Friday, October 30, 2020, 6pm
Link (Passcode
Kenneth Brent Smale
Los Angeles Angels

Transitioning from Academia to Industry: Analytics in Pro Sports
Monday, November 2, 2020, 6pmJeremy Alexander
Victoria University
Monday, November 16, 2020, 4pmDavid Meza
Twenty3 Sport
Tuesday, November 24, 2020, 11amIoannis Ntzoufras
Athens University of Economics and Business
Friday, December 4, 2020, 6pmJulien Guyon

Kenneth Brent Smale – Transitioning from Academia to Industry: Analytics in Pro Sports

Friday, October 30th, 2020
Kenneth Brent Smale (LA Angels, Apex Skating)
Transitioning from Academia to Industry: Analytics in Pro Sports
Zoom Link: https://utoronto.zoom.us/j/6030825347 (Passcode: FrY0ym)

As a student, the bulk of your training in analytics comes in the classroom and is heavily involved in the theory and simple strong signal-to-noise examples. In reality, and particularly in sports, things get much noisier with true data and different personalities and stakeholders. Kenneth Smale will talk through just how analytics differs from academia to the industry and provide guidance on how to make the transition as easy as possible.

Dani Chu – It’s Fun Getting Into (Foul) Trouble

Wednesday, October 14th, 2020, 6:00pm EST
Dani Chu (Seattle Kraken)
It’s Fun Getting Into (Foul) Trouble

This project investigates the fouling time distribution of players in the National Basketball Association. A Bayesian analysis is presented based on the assumption that fouling times follow a Gamma distribution. Methods are developed that will allow coaches to better manage their players under the threat of fouling out.

See a recording of the presentation below.

Abdullah Zafar – Mathematical Modelling in Professional Sport

Friday, October 9th, 2020, 6:00pm EST
Abdullah Zafar (Sports Performance Analytics Inc.)
Mathematical Modelling in Professional Sport

How to quantify actions in sport in order to build metrics, get insights, and drive performance? In this talk, we will overview, compare and contrast approaches using football (soccer) data from the Danish Superliga; focusing on how we can model the movement of a team using flow fields and dynamical systems, derive metrics to quantify team tempo, and then demonstrate the utility and application to the physical training of players as well as team performance as a whole. We will then break down tempo further using topological time series analysis to better understand the dynamics of a football match and highlight the difference in teams during goal-scoring moments.

A recording of the presentation will be made available soon – stay tuned!

2015 Toronto Blue Jays’ Hitters: A PITCHf/x Preview

Written by: Doug Duffy

With the Blue Jays flying north and spring training squarely in the rear-view mirror, Torontonians can leave behind their masochistic winter ritual, watching the Maples Leafs, in favor of their spring ritual, asking “Is the dome open yet?”. Incidentally, in the year 2015, there’s a twitter account for that. Along with the arrival of Opening Day has come the annual barrage of previews, some more quantitative than others. My personal favorite was the series of previews published on Grantland for each of baseball’s divisions, nicely melding projection systems, depth charts and win projections with more qualitative subjects like strengths/weaknesses and storylines. I, however, chose to take the opportunity to dig into the Pitch f/x database for the first time to see what it can tell us about the 2015 Blue Jays hitters, especially the new arrivals. Hopefully, I’ll get around to performing something similar for the pitching side of things soon.

Read more 2015 Toronto Blue Jays’ Hitters: A PITCHf/x Preview

Using Projection Models for 2015 Fantasy Baseball Drafts

Written by: Doug Duffy

If you’ve ever participated in a fantasy draft of any kind, you’re familiar with the concept of projections. Projections, they’re (almost) as simple as they sound. What do you project a given player to accomplish based on his past accomplishments? Projections are not restricted to the realm of fantasy sports however; teams utilize projections as well, to assist them in player valuation. In this post I’ll explain how you can use projections for player valuation for your own fantasy baseball league, using a model based either on Standing Points Gained above replacement, or Fantasy Points above replacement, depending upon the scoring system of the league [1]. In addition, I’ll be posting the R code used to perform the models, as well as Draft Cheat Sheets containing relevant draft info from many of the sources we searched.





Special Request (AL-only 4×4 10 Team no R or K) : 4x4ALonly10Team

Update (3/21/2015) : The projection database and draftsheets have all been updated, and the R code used to calculate TOTspgAR and FPtsAR has been posted. Enjoy.

Read more Using Projection Models for 2015 Fantasy Baseball Drafts

Sports Industry Conference 2015 & Next Meeting

Earlier today the UTSPAN team had the pleasure of attending the 2015 Sports Industry Conference hosted by the University of Toronto Sports and Business Association (UTSB). UTSB were kind enough to let us set up a small booth with a poster to show off a bit of our work and extend an invitation to all attendees. The conference was a big success and we would like to thank UTSB for hosting an extremely well-organized event with top class panels.

We would like to announce that our next meeting will be held on Monday 16 March 2015 at 7PM in room 3008 of the Bahen Centre for Information Technology (40 St George Street). Join us to learn more about the group and what we hope to achieve in the coming months! We will also be hoping to discuss some possibilities for the upcoming UTSPAN Data Hack-a-thon!

A big thank you to everyone who stopped by the booth to chat with us! If you have any questions feel free to reach out to us on Twitter or by email at: sportsanalytics@utoronto.ca

Introduction to Analytics in… Soccer

Written by: Valentin Stolbunov

Soccer, or football, or footy, or “the beautiful game” is the world’s most popular sport. When trying to prove this to a fan of North American sports, a soccer fan’s best weapon is usually global TV audience numbers. The 2014 Super Bowl had an audience of about 160 million viewers worldwide. The same year, the FIFA World Cup final had a global audience of about 1 billion. So, yeah, soccer is popular.

The recent sports analytics movement, however, didn’t originate from the world’s most popular sport. Most would agree it started with baseball and then spread to other North American sports – hockey, basketball, and football (the one with helmets). Compared to these sports, the use of advanced or “fancy” stats in soccer is still in the early stages.

Read more Introduction to Analytics in… Soccer

Introduction to Analytics in… Baseball

Written by: Kurtis Judd

Whether you’re simply interested in following home run races, or using programming languages to predict next year’s MVP, it’s hard to argue that baseball isn’t a statistics driven sport. Every event in the game is so discrete, that it’s a statistician’s dream of clean, easy to work with data.

Read more Introduction to Analytics in… Baseball