Welcome to Toronto Blue Jays Talk Radio (unplugged), a show dealing with baseball matters that do not require in-depth study.
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Caller Harrison: Hey, it’s Harrison from Buffalo. I want to talk about Mitch White.
Radio Host: Go ahead.
Caller Harrison: Do you agree that I, I mean White, pitched better than some of the underlying numbers suggest? I’ll hang up and listen while I finish this Bibimbap.
Radio Host: During his initial stint with Toronto, White pitched better than some of his numbers indicate. Indeed, his 8.17 ERA in six starts (25.1 innings) is awful. According to the Game Score metric, his last three starts averaged 28, which is well below average (the MLB average is 50). It was not a surprise to see the Blue Jays demote White to Buffalo after his September 6 start against Baltimore, during which he lasted less than three innings and was charged with five earned runs. With September’s expanded roster, Toronto could more easily replace White with bullpen days.
However, there are two items to note. First, some people have very elevated expectations about the performance level of a #4 or #5 starter. Second, some metrics support the view that White’s performance was in-line with that of a #4 starter.
Consider Table 1, a framework to classify pitchers into starter slots (#1, #2, etc.). To use the data, ponder a starter with a 2.50 ERA, then he is in the Top 20th percentile and is a #1 starter. If a starter has a 3.25 ERA, the pitcher is a #2. A starting pitcher with an ERA of 5.15 has performed at a #5 starter level. For the FIP and xFIP metrics, the same classification methodology is used to determine a starter’s performance level.
Suppose the Blue Jays expect #4 starter performances from White, reasonable for a playoff-contending team, then White’s FIP is #3 starter calibre, and his 4.62 xFIP is #5 starter grade. White’s ERA is very high. To address this, let’s turn to Table 2. The sample includes starting pitchers with a minimum of 60 innings (159 starters).
Table 2 shows a selection of starters that fall in the #4 starter role based on 2022 fWAR. In other words, of the 159 pitchers, the pitchers selected have fWARs that rank within the 91 to 120 range. These pitchers also play for playoff contenders. According to the expected stats (xISO, xwOBA and xOPS), White compares favourably to the other five #4 starters and the MLB Starter Average.
Yes, the OPS metric is poor. However, consider the minus 4 OAA stat: Toronto’s defence has been below average when White was on the mound. Only Kevin Gausman has been plagued by worse defence (-10 OAA in 152.1 innings). White has garnered a minus 4 OAA in only 25.1 innings! Better defensive support would likely deflate White’s ERA and OPS numbers, mainly because his xISO and xERA are better than the MLB Average. With a better defence behind White, his Game Score numbers would rise, placing him in line with the other #4 starters. Also, the significant xOPS-OPS difference suggests that White has had bad luck. For the record, White’s BABIP during his initial Toronto tenure is 0.379; his career mark is 0.290.
If White returns to Toronto for the balance of September, I think he should perform at a #4 starter level, which will boost the Blue Jays’ playoff odds. Next caller.
Caller Smith: Call me E.D. I want to talk about Jose Berrios. Do you realize that Berrios has pitched much better than many believe? If it were not for some terrible outings, his ERA would be much better. If you remove his six poorest outings (37 earned runs in 17 innings), his ERA would be 3.34, a solid ERA for a #2 starter. What say you?
Radio Host: With the name E.D. Smith, cherry-picking must come naturally to you. No, Berrios has pitched poorly this season. His HardHit% is 11th percentile; his Barrel% is 7th. You don’t produce those numbers in a “few” bad outings.
Consider Table 3, which includes the data from Berrios’s September 12 outing. There is much green on the table. Except for July and September, Berrios pitched poorly in the other four months of the season. In those four sub-par months, batters have hit his pitches hard at a high rate (see xISO).
Berrios’s performance has been aided by above-average defensive support. Among all pitchers, he is tied for tenth-highest in terms of defensive support (+7 OAA).
Thus far in 2022, according to the Game Score metric, Berrios has produced average or better starts in 15 of his 28 starts (54%). Contrast the 54% figure with his 2021 and 2019 seasons. In 2021, 72% of his outings were average or better; it was 69% in 2019.
Let’s come back to the HardHit%. Even in his “good” performances, Berrios’s HardHit% is poor. In 2021, of his 23 average or better starts, 52% (12 of 23) had a HardHit% greater than 36% (the average MLB HardHit% is 35.8%). In 2022, of his 15 “good” starts, 13 (87%) had HardHit% that exceeded 36%. Therefore, in 2022, opponents hit his pitches very hard in good Berrios starts.
Yes, HardHit% is not the only metric to examine. Contact rate and launch angle are essential factors to consider. However, to put HardHit% into context, batted balls with an exit velocity with a minimum speed of 95 mph account for 72%, 74% and 98% of all doubles, triples and home runs, respectively. Hence, examining a pitcher’s HardHit% is critical.
Berrios’s most recent performance is cause for some optimism. However, let’s not cherry-pick the data to create a misleading picture of his 2022 season. This campaign has been disappointing thus far.
Caller Rick: Hey, thanks for taking my call. I want to talk about the Blue Jays failing to sweep the series against bad teams. Championship teams crush the bad teams, especially at home. It’s not the try league; it’s the get-it-done league. You don’t come to my house and win games. You can’t judge a book by its cover.
Radio Host: Huh?
Caller Rick: Sorry, I just went down a cliché rabbit hole. Back to the subject. Tell me why fans of the Blue Jays should not expect a sweep of three-game series against bad teams. Also, I think the Jays will win at least four games in the current five-game series with Tampa. You will need all hands on deck to answer this question. I‘ll hang up and listen.
Radio Host: Fortunately, Producer Lorne, who screened your call, is also an actuary. He has scribbled some notes for me to address the three-game sweep issue and your Toronto-Tampa prediction.
First is the sweep question. Suppose Toronto has a three-game series against the Kansas City Royals. Also, assume the odds of the Jays winning each game is 2:1, which is high but let’s go with it. Therefore, when I apply the binomial theorem, the probability of the Jays sweeping the series is less than 30% (29.63%). In other words, the odds of sweeping a three-game series, even when facing a bad team whose odds of winning in each particular game of the series is 33%, are low.
Next, your prediction of Toronto winning at least four games against the Rays in the current series. Suppose the Jays’ odds of winning each game is 60:40, which is high. Alek Manoah’s win probability is close to 60:40, but do you think the Jays’ odds of winning a game versus Shane McClanahan or Drew Rasmussen will be that high? I don’t.
However, for the sake of argument, let’s use the 60:40 odds figure for the Jays in each game. The binomial theorem generates a 33.7% probability that Toronto will win at least four games against Tampa. If I change the odds of winning from 60:40 to 55:45, the likelihood of winning at least four games is 25.6%. Therefore, winning at least four games in this Toronto-Tampa series is unlikely.
I’ll close with this thought. Baseball results have a degree of randomness to them. Consider the 2021 San Francisco Giants, who won the most games (107) during the regular season. They faced the Dodgers, winner of 106 games, and won 10 of 19 games. However, the Pittsburgh Pirates, winners of 61, were victorious in four of the seven games played against the Giants. Bad teams beat good teams. It’s baseball.
Well, that’s it for today. Thanks for listening.
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Bob was a St. Louis Cardinals fan until the Blue Jays arrived on the baseball scene, although he still has a soft spot for the Cards. Similar to straddling the Greenwich Meridian, as depicted in the avatar, Bob applies sabermetrics when applicable, but his heart tells him that Lou Brock belongs in the Hall of Fame.