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The draft prep process

The analytics team begins its process by collecting data on each draft-year prospect using a variety of metrics and scoring settings.

This data will help them narrow down the players that the Sabres scouts will focus on.

“If you look at the players who are eligible for the draft this season, there are about 32,000 players in our data set,” Barlowe said. “If you include the players from the Plus 1 and Plus 2 draft years who were eligible in previous drafts, it's about 100,000 players – numbers that are difficult to keep track of all at once. A lot of our process is helping – especially in the later round drafts – to reduce those numbers to manageable numbers that our scouts can then keep an eye on.”

While the scouts watch the players, Ventura's team monitors the high-quality data it receives on each prospect. The challenge is deciding how to appropriately weight all of the information that comes from each evaluation situation.

NHL teams look for promising talent playing in over 30 different leagues around the world. Especially in Europe, several factors influence the evaluation in a single season, including the age of the players, the level of competition and tournament participation.

“For some players, we analyze over 10 different rating settings in the two seasons before their draft, simply because of the different leagues and tournaments they play in at different ages,” Ventura said.

The main goal is to find out which players perform consistently in their different rating settings.

“It starts with understanding who the players are at the beginning of the season and gradually updating our opinions on those players as more and more data comes into our systems as the season progresses,” Ventura said.

Ventura's group has developed models that predict players' future performance while giving more weight to certain areas of the game. The process helps Ventura, Galamini Jr. and Barlowe track metrics that players can control, such as effort, to select players who exhibit the traits that correlate with success in the NHL.

“This additional data helps us filter out the players who not only score a lot of goals, but also do all the additional things that are good for success in the NHL – the players you want to have on your team in the playoffs,” Barlowe said.

Benson, for example, met many of the team's criteria even though he was considered an undersized forward in the draft.

“Not only did he provide offensive production as a goal scorer and playmaker, but Zach contributed in many other areas as well,” Galamini Jr. said. “Like winning puck battles, controlling the puck and playing a solid defensive game. He did things that are required at the NHL level and met many of our criteria.”

“But of course it gets tricky when you like some aspects of a player and not others. And that's what happens when you're dealing with selection. You have to live with some of the shortcomings and try to figure out how it all balances out at the end of the day.”

Ventura and his team then independently evaluate each prospect from a purely statistical perspective, using their agreed-upon process and criteria to create their own lists before the larger group comes together. The biggest challenge is avoiding internal bias and remaining objective, using the data to tell the story.

The group agrees not to read scouting reports or watch videos on a player until they have formed a clear opinion based on the data. Often times, the analytics team's opinion of a player is similar to the scouting opinion.

“It's rare that our description of a player differs in any significant way from a scout's description,” Ventura said. “And so I find that our opinion and the scout's opinion are pretty close after we developed the models that we now use to evaluate players and really expanded the depth with which we can look at the details of a player's game.”

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