Using advanced stats to see which Blue Jays could improve regress

Jun 5, 2022; Toronto, Ontario, CAN; Toronto Blue Jays first baseman Vladimir Guerrero Jr. (27) looks to the bench for instructions during an at bat against the Minnesota Twins during the first inning at Rogers Centre. Mandatory Credit: John E. Sokolowski-USA TODAY Sports
Jun 5, 2022; Toronto, Ontario, CAN; Toronto Blue Jays first baseman Vladimir Guerrero Jr. (27) looks to the bench for instructions during an at bat against the Minnesota Twins during the first inning at Rogers Centre. Mandatory Credit: John E. Sokolowski-USA TODAY Sports /
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With two months of the 2022 MLB season already in the books, we’ve been able to gather a much larger sample size of statistics that can accurately reflect a player’s performance. Some Blue Jays, like Alejandro Kirk, who currently has an OPS well above .800, have put up some great raw numbers this season, while others like Bo Bichette, who’s struggling to stay above .700, have had a harder time putting up numbers so far this year. Basic stats like OPS, batting average, or even ERA often don’t tell the full story this early in the season though, and advanced stats (often referred to as peripherals) can be a great resource to help project players over the course of a full season, or even explain certain players’ performances to this point.

A brief explanation of advanced stats in this context

I feel like advanced stats or peripherals are terms that are thrown around a lot when talking about stats these days, but it’s not always necessarily clear what they are. When talking about advanced stats (often referred to as sabermetrics) in relation to underlying numbers, people are usually referencing the stats you’ll find on sites such as FanGraphs or Baseball Savant.

FanGraphs generally uses stats like wRC+ to measure raw offensive production, but utilizes other stats like ISO and BABIP to help measure expected production (here’s their offensive glossary). For pitching, they’ll mainly use stats like FIP and xFIP to measure expected pitching performance (pitching glossary). Baseball Savant uses the recently introduced, statcast statistics to place player’s performance in categories from expected batting average to average exit velocity on a percentile scale to create a chart that helps give a good idea of a player’s expected performance.

There are obviously certainly outliers who, despite having weak expected stats, still perform well, but generally the players with good expected numbers are the ones with good raw numbers, over the course of a full season. With that all out of the way, let’s take a look at what the advanced statistics say about certain Blue Jays.