MLB Pitcher Advanced Metrics Studs and Duds - Season Recap

Connelly examines previous fantasy baseball pitcher studs and duds articles to review key takeaways for Week 25.

Welcome back to fantasy baseball and RotoBaller’s Statcast Pitcher Studs and Duds article series! Each week, I have selected one advanced metric, chosen two pitchers with strong values and two with poor values, and analyzed what those values may mean for future performance.

Sadly, we have come to the end of another fantasy baseball season and the end of this season's series. I have covered plenty of interesting players, stats, and trends, which hopefully helped some of you throughout the season.

Rather than choose a final metric, I am going to review the entire series and highlight some fantasy takeaways and players who exemplified them. It has been great diving into pitching metrics for another season to help inform fantasy decisions. Thanks to everyone who followed throughout and I'll see you all in 2023!

• Fantasy baseball trade analyzer
• BvP matchups data (Batter vs. Pitcher)
• PvB matchups data (Pitcher vs. Batter)
• Who should I start? Fantasy baseball comparisons
• Daily MLB starting lineups
• Fantasy baseball closer depth charts
• Fantasy Baseball live scoreboard
• Fantasy baseball injury reports

Fantasy Baseball Pitcher Takeaways

All stats are current as of Sunday morning, September 25, 2022.

Pitchers Can Outperform Their Underlying Metrics

The first takeaway is that even the strongest underlying metrics may never materialize into actual performance metrics. A Mariners starter and Giants starter highlight both ends of this.

While not fantastic, Marco Gonzales has been a serviceable fantasy option this season. Gonzales has gone 10-15 with a 4.05 ERA, 1.33 WHIP, and a 12.9% strikeout rate. Gonzales appeared in this series in Week 10 as an xERA DUD and in Week 24 as a SIERA Dud. Gonzales' numbers did regress as expected as the season progressed, but not to the degree expected.

His current 4.54 xERA is still half a run above his ERA, and his 5.02 SIERA is almost a whole run higher. Gonzales' fantasy shortcomings are known, but despite his underlying metrics, he hasn't had an ERA above 4.05 since 2017.

On the other side of things, Alex Wood (shoulder) has a lackluster 8-12 record with a 5.10 ERA, 1.24 WHIP, and 23.6% strikeout rate. That being said, he made it into the Week 17 article as an xFIP Stud. The injury of course throws things off, but Wood's 4.01 xERA, 3.41 xFIP, and 3.46 SIERA are all much lower than his ERA and are in line with his 2021 performance.

The takeaway here is that underlying metrics can be used as potential indicators, but there is no guarantee that things will end up reflecting them. Analyzing underlying metrics gives fantasy managers the upper hand, but they may not end up aligning with actual results every time.

But Underlying Metrics Are Great For Analysis Nonetheless

As I just pointed out, analyzing underlying metrics doesn't always pan out, but we do it because it can pay big dividends. Fantasy managers can get ahead when they hit on buy-low or sell-high candidates. San Francisco Giants starting pitcher Alex Cobb is my main example of this from this season.

Cobb currently has strong numbers overall this season, with a 6-7 record, 3.67 ERA, 1.27 WHIP, and 23.7% strikeout rate. He made the Week 9 article as a Brls/BBE% Stud and the Week 19 article as an ERA-xERA Stud but had a 5.73 ERA in Week 9 and a 4.15 ERA in Week 19.

Both times I called Cobb a buy-low candidate, suggesting that his underlying numbers indicated potential positive regression. I even acted on this myself in one of my leagues, trading for Cobb before the trade deadline. In this case, Cobb's signs were present just a few months in, leaving plenty of time to benefit.

Cobb is just one example of this. Fantasy managers have to find any edge they can get, and looking beyond peripheral numbers is usually a solid approach to achieving this.

One Stat Does Not Paint A Complete Picture

This may sound obvious, but it is often difficult to get a full picture of a player by looking at a single metric. Two specific examples of this came in Week 3 with Adam Wainwright and in Week 19 with Dylan Bundy.

I wrote about Wainwright as a swinging-strike rate dud. Even early in the season, I concluded that Wainwright still profiled as a solid fantasy option given his other skills. I would argue that this was the case, as the veteran is now 11-10 with a 3.51 ERA, 1.24 WHIP, 18.1% strikeout rate, and just over six innings per start.

On the flip side, Dylan Bundy made the series as an ERA-xERA Stud. I concluded then that Bundy's batted-ball profile was more damning than his 3.86 xERA and that he was not worth buying into. This turned out to be a good choice, as Bundy now has an 8-7 record with a 4.93 ERA, 1.25 WHIP, and 16% strikeout rate with an increased 4.18 xERA.

Like anything, it is helpful to have a full understanding of a situation before taking action on it. Baseball offers all kinds of statistics for fantasy managers, and one alone cannot provide all the answers. We need to be wary of jumping to conclusions based on one metric at one point in time.

Trust A Clear Picture If It's There

Part of the difficulty is making meaning of the various underlying metrics vs. the peripherals. This can make it easy to over-analyze different aspects of pitchers' profiles. Sometimes, the numbers simply are what they are and there is no need to look further.

In my second-half preview article, I highlighted two strong and two weak Statcast profiles. I highlighted Cristian Javier and Alex Cobb as Statcast Studs and Jose Berrios and Madison Bumgarner as Statcast Duds.

Fantasy managers could have tried to buy low on the Duds or sell high on the Studs with half a season to go, but they would have likely gotten burned had they tried to act on these pitchers. In the end, each pitcher provided what their Statcast profile suggested.

The point of comparing underlying and peripheral metrics is to identify discrepancies and take advantage of them. Sometimes, all of the numbers agree with each other. These instances are ones that fantasy managers should take at face value, rather than trying to find further meaning in them.

More Sabermetrics and Statcast Analysis