Recommended Reading

There are a huge number of excellent articles on the internet on a vast range of topics. However, finding these gems can be difficult at times. This is by no means even scratching the surface of what is out there, but I thought I would just keep a collection of articles that I found particularly interesting or useful. So, here they are:

TENNIS

STATS & BETTING

The Implications of Winning a 5 Set Match - Dan Weston (@tennisratings)
Rafael Nadal - A Problem of Bad Variance - Dan Weston (@tennisratings)
Do Players get broken more often after failing to convert break point? - Jeff Sackman (@tennisabstract)
The Limited Value of Head-To-Head Records - Jeff Sackman (@tennisabstract)

MAINSTREAM MEDIA

Andy Murray is a Tennis Nerd - Tom Perrotta (@tomperrotta)
Game, Set, and (Fixed) Match - Ben Rothenberg (@benrothenberg)
I Lost to Redfoo: A Tennis Story - Paul Wachter

OTHER

Slam Junior Champion? Your Future as Tennis Pro is not Assured - Stefano Berlincioni (@carretero77)
Junior Grand Slam Winner and Pro Career: What About Girls? - Stefano Berlincioni (@carretero77)

FOOTBALL

EXPECTED GOALS

Premier League Projections - Michael Caley (@MC_of_A)
Gladbach: Luckiest Team in Europe or a Blind Spot in Expected Goals? - Saturdays On The Couch (@SaturdayOnCouch)
Expected Goals and Support Vector Machines - Martin Eastwood (@penaltyblog)
Shots and Key Passes are Better than Goals and Assists - Alex Olshansky (@tempofreesoccer)
A Close Look at my new Expected Goals Model - Sander Ijtsma (@11tegen11)
Why using stats properly could be more important than scoring goals - Raphael Honigstein (@honigstein)

ELO RATINGS

Applying ELO Ratings To Football - Martin Eastwood (@penaltyblog)

OTHER

How data, not humans, run this Danish football club - Michiel de Hoog (@michieldehoog)
An Introduction to the 'Per 90' Metric - Ben Pugsley (@benjaminpugsley)
Analysing Football Teams Using Cluster Analysis and Principal Component Analysis - ???

MODELLING AND DATA

It is all about the Data! - Matthew Trenhaile (@crazedalchemist)
Models, Simulations, Systems and Trends - Matthew Trenhaile (@crazedalchemist)
Analytics, not statistics, driving NHL evolution - Arik Parnass (@arikparnass)
Hockey Analytics Needs More Theory, Not Just More Data - Draglikepull (@draglikepull)
From Microsoft to the MLS - Taylor Soper (@taylor_soper)


CODING AND MODELLING SKILLS

How To Use R For Sport Stats (Part 1, Part 2, Part 3) - Brice Russ (@KilroyWasHere)

VIDEOS

Intro To Soccer Analytics Course - Chad Murphy (@soccermetric)
West Ham aren't as good as you think they are - Joel Salamon (@messiseconds)