r/baseball • u/Swimming-Reindeer-39 New York Mets • 1d ago
Analysis Despite his mechanical changes and surface-level success with the Rays since August 26th, many of Freddy Peralta’s underlying stats remain quite similar to his bad stretch with the Mets.
Disclaimer: No this is not coming from a salty Mets fan despite my flair. I am happy that Freddy is having success, but there are extremely important caveats to that success.
Ever since August 26th, it may seem like Freddy Peralta is one of the best pitchers in baseball if you just look at ERA. However, for all that has been made about Peralta’s latest string of success, it is noteworthy how many of his underlying peripherals have gone effectively unchanged.
Comparing ERA, FIP, xFIP, and SIERA
Freddy Peralta 3/26 to 8/25: 5.33 ERA / 4.66 FIP / 4.36 xFIP / 4.34 SIERA
Freddy Peralta 8/26 to 9/25: 0.79 ERA / 2.78 FIP / 4.44 xFIP / 4.27 SIERA
Freddy Peralta’s Postseason: 0.84 ERA / 3.76 FIP / 4.94 xFIP / 4.43 SIERA
Despite far lower ERAs through the last two periods, Peralta’s FIP doesn’t change as much and his xFIP and SIERA remain virtually identical across all three periods. That is notable, since xFIP and SIERA are stats that claim to account for elements “within pitcher control” that ERA can’t fully capture. If xFIP and SIERA say that Peralta has been the same pitcher for basically the entire year, what is causing them to disagree with ERA so much?
xFIP and SIERA usually try to account for Left on Base %, BABIP against, and Home Run to Fly Ball rate. SIERA more actively tries to take batted ball distribution into account, while xFIP just normalizes HR/FB rate within the normal FIP stat. These peripheral stats try to account for things that may be considered “luck-based” for a pitcher. And when examining these peripheral stats for Peralta, they certainly paint a picture of a pitcher who was getting extraordinarily unlucky before now getting extraordinarily lucky.
More peripheral stats (for outcomes the pitcher doesn’t typically control themselves):
Freddy Peralta 3/26 to 8/25: 67.0% LOB / .311 BABIP / 13.6% HR/FB
Freddy Peralta 8/26 to 9/25: 94.0% LOB / .187 BABIP / 2.2% HR/FB
Freddy Peralta’s Postseason: 100.0% LOB / .207 BABIP / 5.9% HR/FB
Freddy Peralta’s strand rate (LOB%) after August 26th is absurdly high, and is way higher than any qualified pitcher in that timespan by a long shot when the league-average is 72.3%. It isn't uncommon to see ace pitchers maintain high strand rates in a season, but it is still luck-based enough to the extent that fluctuations in small samples can heavily affect ERA.
Maintaining low BABIPs is more controllable, but it is rare for it to hover around or below .200 over a larger sample. It is also more suspect with Peralta given that he has never been much of a groundball pitcher, but improved stuff can definitely still help with this if it decreases hard hit rate. This is also why xERA (which isn't listed here) has improved given worse quality of contact against, even if the batted ball distributions that go into SIERA doubt that it can sustain itself. Improved defense can also help with lower BABIPs.
HR/FB rate usually hovers around 11%, and it is generally not expected for a pitcher to maintain rates that are wildly below or above that mark for an extended period of time. However, small samples can produce low HR/FB rates that paints a more rosy picture of a pitcher’s ability.
tl;dr: Even if Freddy Peralta has improved as a pitcher on the Rays compared to the Mets, that improvement is being heavily obfuscated by stats that indicate that he is getting highly lucky across this specific sample of starts. As a matter of fact, certain peripheral stats don’t actually believe he is a very different pitcher at all. His true pitching ability is somewhere in between his Mets self and his Rays self.
16
u/cabose7 New York Yankees 21h ago
Throwing upper 90s since he joined the Rays probably has helped the results