The most difficult time in an MLB career is now for Guardians’ young hitters.
Baseball is a game of constant adjustments, and those adjustments are almost never more volatile than after a new MLB player has their first hot stretch in the show. Today we’re going to discuss what to expect going forward with some of the young hitters on the Guardians roster this season. Specifically, we’re going to look at the youngest hitters currently playing almost every day on the roster: Chase DeLauter, Travis Bazzana,
Brayan Rocchio, Angel Martínez, and Kyle Manzardo. In looking at them, I’d like to take you through the early careers of some veteran players that ended up becoming superstars, and consistent MVP contenders. We’re also going to break down results vs. process and what to look for that may cause concern.
First, let’s look at some examples of some modern superstars in their rookie season, and a very recent Rookie of the Year winner. For this section, we’re just going to look at the results because this will establish an important premise we need for later on. First, let’s take a look at Bryce Harper in 2012. Bryce Harper started the first 8 games of his career with a .924 OPS. The next 12 games it was .625. The next 20 games it was 1.144. For the next 55 games his OPS was .563, and he finished that season putting up a 1.044 OPS in the final 44 games. We can already see that even a multitime MVP/All-Star/Silver Slugger winner that broke into the league as one of the most highly anticipated MLB prospects in a very long time had a lot of ups and downs in their first season.
Another MVP and Rookie of the Year recipient, Ronald Acuña Jr., had a similarly up and down Rookie of the Year campaign. He got off to a very hot start, hitting to a 1.289 OPS in his first 5 games, but quickly cooled off. In his next 22 games, his OPS was only .609, and in the 16 games after that it was a respectable, but underwhelming for the young star, .764. After that, he went on a tear over the next 53 games, with an OPS of 1.134, before cooling off for the final 15 games with an OPS of just .652.
Lastly, let’s look at the reigning AL Rookie of the Year winner Nick Kurtz’s 2025 season. Unlike the others, he got off to a very slow start. In his first 23 games, his OPS was just .558. The next 22 games it was 1.107, and the 22 after that it was an unbelievable 1.478. He then cooled off for a bit. His next 14 games only saw him have an OPS of .693. The next 17 games it was 1.227. After that, for 15 games he cooled off again down to an OPS of .708, and he ended the season with a 1.228 OPS in the final 4 games.
In just these three examples, we see extreme swings within each hitter. Sometimes lasting only a few weeks, but sometimes lasting multiple months. We can’t determine a lot from OPS results on their own because they are incredibly noisy. A lot of factors can cause big swings in a sample size even as large as 20 games. It could be having several games in a 20 game stretch where you face the top 2 pitchers in every team’s starting rotation. It could be the hitter overswinging or chasing out of the zone more. It could even be a week of cold humid weather causing a handful of balls that would be extra base hits under normal conditions getting knocked down by the wind and being outs instead.
All of this is to say that these OPS results alone don’t tell us much apart from “it might be time to take a look under the hood and see if we’re doing something wrong,” and these examples are just to illustrate that even the best hitters go through major ups and downs, especially as rookies.
There’s going to be a lot of data to look at coming up, so first I want to briefly explain how it’s all organized. For each of the five Guardians players we are looking at today, I’ve given each their own table. Each player has had their season broken down into 4-5 buckets of games purely by OPS results. For each bucket, we are going to be highlighting 7 statistics (not including the OPS) for each bucket. The stats are grouped into 4(ish) layers. We start with Layer 1: Swing Decisions. Next is Layer 2: Contact Ability. The next layer I have listed as Layer 2.5: Bat Speed. This is put between layers 2 and 3 because it doesn’t truly fit with either one, but is an important bridge that connects the two layers. Next is Layer 3: Contact Quality, and last is Layer 4: Results. Now that we have established how all the data we will be looking at is organized and what statistics we are looking at, I will put the tables for all 5 players below. The individual statistics will have definitions and explanations at the end for clarity.
We can see that each of these young hitters is going through ups and downs. The first thing I think we can all see is the difference between the true rookies (Chase and Bazzana) and the young hitters that already have a few seasons under their belts. We can see in general that the rookies’ numbers are overall significantly more erratic, and the stat where that stands out the most in my mind is bat speed.
Both Chase’s and Bazzana’s average bat speeds swing wildly, with differences up to and even over 2 mph. But if we look at Manzo, Angel, and Rocchio, they are consistently within a 1 mph range. If we look in layers 1 and 2, we can see that the 3 young hitters with more experience have similarly clustered numbers in those categories, with maybe 1 outlier, and this is where we can also see Chase separating himself from Bazzana a bit.
Chase’s Whiff and Chase rates in his most recent 3 buckets are all much more tightly clustered and a decent chunk lower than his first bucket, but Bazzana is seeing some spiking in chase and in whiff for his most recent two buckets. I believe this already illustrates very well how volatile early career MLB adjusting is for hitters, and shows how just a couple seasons of experience flattens out underlying metrics quite a bit.
This is not to say that an even more experienced hitter won’t go on a stretch where their chase rate skyrockets 12 points, but more that those outliers become more rare. This example, though, is the first of one of our previously listed types of slumps – one caused by plate approach deterioration.
When talking about our Rookie of the Year examples earlier, we mentioned one potential type of slump we see hitters go through is because they start over swinging or chasing more out of the zone. That could be considered a plate approach deterioration slump. In bucket four, Travis Bazzana’s Chase% and Whiff% have both increased significantly, and we see the OPS result within that bucket has gotten quite poor. It would be reasonable to think that’s a likely cause of the slump. Swinging at more pitches out of the zone leads to more swings and misses, and when you do make contact on those pitches, it is often weaker contact. Less and weaker contact in general leads to fewer walks and hits, and that of course leads to lower OPS numbers.
Is this cause for concern? Well, the short answer is probably not. Ultimately, this bucket is just 10 games. This very easily could just be a bad couple weeks, and he could make some adjustments and get the numbers back under control. Variations like this in a rookie season are incredibly normal, and they don’t really become a concern unless the same numbers do not improve or get worse over an extended period of time.
Now that we’ve seen how approach deterioration can lead to a slump, we can move on to the next layer. If we look at Chase’s second and third buckets, we can see Chase% difference is only 0.5, and Whiff% difference is only 2.6. The Z-Contact% difference is a bit larger here, but both numbers are still fairly close together. So the approach looks very consistent, but the OPS difference is massive. Over 850 points! What’s going on here?
This brings us to our next potential type of slump – a contact quality slump. When looking at these two buckets, we can see the Hard-Hit% difference is massive, as is the average exit velocity, and the xwOBA difference. What we’re seeing here is significantly worse contact quality. This is where it gets a little less visible in traditional stats. We see the lower velocity, but what causes it? This is where variance comes into play. Sometimes in baseball, being an extra 5-10 milliseconds too late or too early can be the difference between a home run and a foul ball. Sometimes, the contact point on the ball being just a few millimeters to high or too low can be the difference between a HR and a warning track flyout, or the difference between a hard low liner between infielders for a hit and a ball hit into the ground more that loses enough speed for the fielder to reach it and get a forceout. These small differences aren’t always immediately obvious either, but being just out of sync with your swing path or slightly off timing wise can result in massive differences in results as well.
So what we may be seeing here is Chase was maintaining a consistent approach over the span of both buckets, but in the second bucket the swings started being a lot more flush with the ball and resulted in much higher contact quality and better results.
The last example I want to look at today is Manzardo’s bucket two and three. We look at his swing decisions, and he’s chasing 5.5% less. Now we look at contact ability: he’s swinging and missing 11.1% less and making significantly more contact in the zone. The contact quality looks significantly better too. Hard-Hit% skyrockets, average exit velocity takes a big jump, and xwOBA increases by nearly 100 points. This looks like a huge improvement across the board, but when we look at the OPS, it’s actually gone down almost 100 points. How is that possible?
Well this brings us to the final example of slumps we see – a luck slump. Sometimes in this sport, you can do everything right and still not see successful results in the box score. Now we’re looking more at the factors that are largely considered out of the hitter’s control – things like strong winds or exact batted ball placement. Sometimes, a hitter will hit a long flyball that on a normal day is a home run, but because it’s extremely humid or cold and windy, the ball just dies on the warning track. Other times, a batter might hit a scalding line drive, and a fielder will make a diving catch and rob the hitter of a hit or even an extra base hit.
When we look at those two Manzardo buckets, this type of result is consistent with these and similar factors, and ultimately these are the type of slumps that should be the least concerning. What we’re effectively saying here is the hitter is doing everything in their power very well, but just hasn’t gotten positive results. For some, this can feel like the most annoying type of slump because it really is largely out of the hitter’s control. But since it is outside of the hitter’s control, all you can do is hold the line and hope the luck swings back your way.
With young hitters, we see a lot less consistency in layers 1 and 2, and we see that especially in the rookie hitters. Now I have one more data table to share. This one is by far my favorite. I’m not going to go in depth on this data as much as the previous set, but I want to share this to illustrate the larger point. The next table is from José Ramírez’s 2024 campaign.
It is obviously incredibly unfair to hold most other players to the standard of José Ramírez, but I think his buckets here are a great example of how as good hitters develop and learn the league, you start to see layers 1 and 2 have much tighter distributions. Better hitters will have very few outliers in these layers, and you start to see a lot more variance in layer 3. We see this trend beginning to show itself also in the non rookie hitters we looked at before.
So what should we expect from these young hitters going forward? For the rookies, it’s very possible we see a lot of ups and downs going forward. After all, that’s what happened with the three Rookie of the Year winners we looked at before. One of the most important things we’ve learned is that not all of the downs are created equally. The next time we see one of these hitters going into a little bit of a downswing, we can break it down, see what type of slump we’re looking at, and determine how concerning the slump is.
I believe that as long as the young hitters can stay focused on getting that consistency in their approach and can minimize the layer 1 and 2 slumps, they’re taking a very important first step into solidifying themselves as legitimate big leaguers.
Stats:
Chase%: The percentage of pitches a batter sees outside the ABS strike zone that they swing at
Whiff%: The percentage of pitches a batter swings at and does not make contact
Z-Contact%: The percentage of pitches in the ABS strike zone a batter makes contact with when swinging
Hard-Hit%: The percentage of batted balls with exit velocities of 95 mph or higher
