Post by countryboy on Mar 7, 2022 23:26:46 GMT -4
There's been an uptick in discussion about advanced stats and analytics on these boards lately. We are starting to learn how teams are using the Instat service, but there is limited availability for the casual fan to explore advanced statistics.
I started to take an interest in advanced stats about 4 years ago. It is a tough field to try to get an introduction to. There's very limited information out there with the "basics" on how advanced stats are collected and used. Furthermore, there is a huge volume of different measures that are out there and there's no one place to find all the information you'd ever thought you'd want to know.
I am an Oilers fan and my understanding of advanced stats has been heavily influenced by what I read from Allan Mitchell of the Lowetide Blog. For those who are readers on The Athletic, Allan is a regular contributor who writes about the Oilers.
When you try to study any advanced statistics in the QMJHL, there are two important pieces of information that are not available to regular fans.
1. Some advanced stats are on a "per 60 minutes" basis. The Q does not publicly track ice time, so there's not a way to study anything in this area.
2. Many advanced stats are on ice metrics. That is, a player gets a credit when he is on the ice for a Corsi, Fencwick, High Danger Scoring Chance, expected goal, etc. These types of numbers are also not publicly shared by the Q.
On metric that I do place in high regard is 5 on 5 goal differential. Basically, it like you take the ingredients of +/- and create a GF-GA ratio when players are on ice. I know +/- sometimes gets a beating since it is heavily influenced by the quality of the team. It's a lot easier to have a good +/- on a good team. Still we all understand you can be +2 in limited game action but also by having the highest ice time on the team. The 5 on 5 goal differential allows you to see who is "tilting the ice" for their team and participating a lot in their team's offense... or I guess at least they are on the ice when their team is scoring.... or being scored against.
So heading into this season, I just wanted to try to see if I could collect some of this data. The Q website tells who is on ice for each goal scored. I started thinking that I could track the Maritime division. But then I thought it would be interesting to monitor a few 2022 draft eligible players. It soon would become clear to me that I'd be tracking the measure for the entire league... or at least I'd give it a try. It's been a fun project so far but it has been a lot of work. I do feel that I'm learning more about players contributions to their teams.
My limitations on this project are that I'm not terribly tech savvy. I know that a database or a spreadsheet might be my best took to collect the data, but I'm not terribly knowledgeable with either of these types of software. I decided to do my data collection using pen and paper and then I summarize my information in a Google Doc at the end of each month.
I've included a link below to my Google Doc that I store my data at the end of each month. Now that I have data for Oct, Nov, Dec, and Feb, you start to see clearer of how is influencing what in the league. When looking at the numbers, it's important to look a players GF-GA relative to his team. It's one thing to have a good measure on a strong team like Charlottetown. It's an entirely different thing to be putting up strong numbers on a weaker team. Thus I've included each team's monthly GF-GA to give a good measuring stick for individual players.
Since I've started collecting, I've shared with a few people, but I know that there are lots of great fans on here who might have some interest in looking at this information.
Here is a link to my Google Doc:
bit.ly/3tEUOFv
I started to take an interest in advanced stats about 4 years ago. It is a tough field to try to get an introduction to. There's very limited information out there with the "basics" on how advanced stats are collected and used. Furthermore, there is a huge volume of different measures that are out there and there's no one place to find all the information you'd ever thought you'd want to know.
I am an Oilers fan and my understanding of advanced stats has been heavily influenced by what I read from Allan Mitchell of the Lowetide Blog. For those who are readers on The Athletic, Allan is a regular contributor who writes about the Oilers.
When you try to study any advanced statistics in the QMJHL, there are two important pieces of information that are not available to regular fans.
1. Some advanced stats are on a "per 60 minutes" basis. The Q does not publicly track ice time, so there's not a way to study anything in this area.
2. Many advanced stats are on ice metrics. That is, a player gets a credit when he is on the ice for a Corsi, Fencwick, High Danger Scoring Chance, expected goal, etc. These types of numbers are also not publicly shared by the Q.
On metric that I do place in high regard is 5 on 5 goal differential. Basically, it like you take the ingredients of +/- and create a GF-GA ratio when players are on ice. I know +/- sometimes gets a beating since it is heavily influenced by the quality of the team. It's a lot easier to have a good +/- on a good team. Still we all understand you can be +2 in limited game action but also by having the highest ice time on the team. The 5 on 5 goal differential allows you to see who is "tilting the ice" for their team and participating a lot in their team's offense... or I guess at least they are on the ice when their team is scoring.... or being scored against.
So heading into this season, I just wanted to try to see if I could collect some of this data. The Q website tells who is on ice for each goal scored. I started thinking that I could track the Maritime division. But then I thought it would be interesting to monitor a few 2022 draft eligible players. It soon would become clear to me that I'd be tracking the measure for the entire league... or at least I'd give it a try. It's been a fun project so far but it has been a lot of work. I do feel that I'm learning more about players contributions to their teams.
My limitations on this project are that I'm not terribly tech savvy. I know that a database or a spreadsheet might be my best took to collect the data, but I'm not terribly knowledgeable with either of these types of software. I decided to do my data collection using pen and paper and then I summarize my information in a Google Doc at the end of each month.
I've included a link below to my Google Doc that I store my data at the end of each month. Now that I have data for Oct, Nov, Dec, and Feb, you start to see clearer of how is influencing what in the league. When looking at the numbers, it's important to look a players GF-GA relative to his team. It's one thing to have a good measure on a strong team like Charlottetown. It's an entirely different thing to be putting up strong numbers on a weaker team. Thus I've included each team's monthly GF-GA to give a good measuring stick for individual players.
Since I've started collecting, I've shared with a few people, but I know that there are lots of great fans on here who might have some interest in looking at this information.
Here is a link to my Google Doc:
bit.ly/3tEUOFv