Jason Ross

Houston would be...fine. He's kind of boring in that he's not like super-fun upsidey like Gage Wood or Kyson Witherspoon could be. He probably is far more likely to be an MLB player than most other picks in that range due his defense. BA has some data on the batted ball profile, the EV's aren't extremely great, but his contact% and especially against velocity is really high. He's pretty passive in the zone so you could point to this and say that the batted ball data and the power would improve even more than it has if you get the guy to swing at the meatballs more often. FWIW, the staff at BA just had a draft and they took Houston above the Cubs pick at 14. The pick was made by Peter Flaherty (Pontes took Aloy at 17) He's a different player than Nico Hoerner in most ways, but he feels like Nico Hoerner did a few years ago; I wasn't wowed by the pick, the upside felt a little limited, but lo-and-behold not only has Hoerner's defense carried him to the majors, his strong contact ability and profile has made him one of the most successful pros in the draft. Houston has that kind of feel to him; whomever picks him won't be super wowed by anything, but you give it a few years and he's starting at shortstop by late 2027 for someone. Especially in this draft, which feels a little less exciting than previous drafts (especially in the mid-late-first rounders), I don't think I'd hate a Houston pick if you liked your ability to continue to add to his power. Go get your fringey-skill, bigger upside picks in rounds two-through-four or something.

Yeah, I really liked his start. I don't want to spoil anything, but have an article in the can looking at what he did during that appearance. Some new data points and tried some new things to effect. I do think he could be moved in July, but I wouldn't be mad if they didn't!

Right. When I said that, it's a league average type of a thing. When I say "we know you'd hit .290" it isn't "every player hits .290 and any difference is unlucky" but that "over the course of the last five years BABIP is pretty stable, so any important deviation from .290 suggests something". That something can be that you are a bad hitter; weak contact=worse BABIP (usually). It can mean you're fast, so you have a higher BABIP. It could mean luck or bad luck. It can mean a bunch of things. Then we can factor in our career BABIP and career batted ball data. It's a deep well. As I said, BABIP on it's own tells us a little. But BABIP with context tells us a ton.

At the very least, I would guess he piggy backs 3-4 innings sometime around Thursday. I have an article in the can on the stuff he did last night, but there was some cool new wrinkles in his game. I'm interested to see more.

I think there was some discourse pregame about Karl Ravech, too. NSBB Bingo!

I honestly do not know what they're doing. The reality is with the amount of data and analytics we have now a days, most orgs make most of the right decisions most of the time. The difference between whatever you perceive to be the 7th best FO and the 23rd best FO is pretty thin when we take it all into account. Data, and the understandings we have now, generally homogenize decisions. You'd have to basically spit on widely accepted norms. The Rockies don't just spit on those norms, they ignore them entirely.

BABIP has no subjective probabilities, it's literally just "batting average on batted balls in play" or "what is your batting average when you hit the ball fair, but it's not a home run?". It erases things like strikeouts and home runs from the equation but still counts all of your singles, ground balls, doubles, popups, etc; as long as it is "in play". While there's no "guaranteed BABIP" league BABIP runs, pretty standard. Let me prove that Here are the last five years league BABIP: .291 (2025), .291 (2024), .297 (2023), .290 (2022), .292 (2021) Basically, we know that if you hit the ball in play, you are likely going to hit like .290 regardless of the year. Even during the steroid era, BABIP was .300 (1998), and .302 (1999)! It only affected things by .10. Where BA's dip, dive and change are in things like when we factor in strikeouts and home runs. If one player strikes out a lot versus one who doesn't, then we see the overall BA change because we were ignoring those things. If one guy has a K% of 30% and another at 20%, they can have the same BABIP but vastly different BAs. We can also increase BABIP by being fast (beat out infield singles) or lower it by being slow. And batted ball data, like launch angle, hard hit%, barrel % all can help earn it. So what we can do is look at someone with, say, a .260 BABIP and diagnose it. If it's a big slow guy who hits a lot of weak contact, that's probably a somewhat earned BABIP. But if a fast guy makes a lot of hard contact is running a .260 BABIP, we can squint and go "hmm, that doesn't make sense". Situations like that suggest for whatever reason, he's probably *not* getting the results he should! Things like xwOBA and xBA (the x stands for expected) are determined through statcast. These won't show up in BABIP, but in other data. Basically, statcast can take the exit velocity, tilt, launch angle, and determine, compared to what normally happens on that exact outcome, how often you should expect a ball to land for a hit. If you hit the ball 105mph on a line, that's usually a hit. If you hit it, instead, right at 3b? That's bad luck, not impossible but bad luck. It's possible for those things to add up and be meaningful, especially at lower sample sizes. I hope that help to answer your question. Thanks for asking! It feels like it's a lot to digest, but really it boils down to our ability to use all the tools we have and figure out if you're doing the right things at the plate, you should have results that follow it. BABIP on it's own isn't super useful, but BABIP, combined with other things can help us paint a picture to help us predict what will happen next. Just because you got a single before, doesn't mean you will continue. By using these model we can more accurately predict who's going to continue to hit, and who won't. (And like I said, I promise there are 29 teams who are using predictive models).

Two things: 1. Recently in Iowa, he had been hitting 94 pretty consistently and averaging 93. So he's throwing harder 2. He only went 40 pitches. Can probably add 1-2mph from the BP Regardless, he's throwing harder than when we first saw him sit in the 91-92 range.

Social Studies, actually! (And I even learned what SOHCAHTOA stood for this year. So math, watch out, here I come).

There is no rudeness here, all kindness; if it's not that, then what is your diagnosis? To clarify, once again over this span he has: maintained typica barrel%, launch angle, and hardhit%, normal walk and strikeout rates. All of his expected data say he's supposed to be hititing around .25 points better than what he is. His BABIP over his last run is .179, which is, unsustainable. Only two hitters in baseball have a lower BABIP in that run, The lowest qualified BABIP in baseball in 2025 is .208, which is at roughly 30 points higher. Last year the lowest sustained BABIP was .225, which is .45 points higher (give or take). If his BABIP over the last 115 PA's was the worst in baseball last year, he'd have .nearly.40 points on his batting average between then and now. Because if it isn't luck and the ball just not landing, it has to be something. There is no magic.

So, there's a pretty obvious understanding in MLB now a days that power fastball / slower curve is a bad combo. Think...Ben Brown. His "deathball"/knuckle curveball gets thrown 90mph or so. Dollander, about a month ago, begun leaning super heavy into the curve, and it worked...for a bit. Lately he's getting crushed. Likely? hitters weren't expecting it, because...why would you do that? Then they got ready for it. Problem with slow-curve (80 mph or so) and mid 90's fastball is that hitters can usually pick up the velo drop on the two pitches easily. And go figure, MLB teams are not biting on the curve at all once they updated the scouting report. Even worse; Coors affects breaking balls and their movement. He's also using sinker, almost exclusively, to lefties. Sinkers have bad R-L splits. It's a pitch you throw to like-hand, not opposite hand. You either speed the curve up and go "deathball" or you use his arm angle (he's very flat) to create natural cut to get lefties and go slider/sweeper heavy to play off of it. He has a great slider! It's all just bad pitching development.

Frankly, what the Rockies are doing right now might be worse. I read a recent article on what the Rockies are doing to Chase Dollander, and it basically flies in the face of everything you would do for a power arm like Dollander. Any team in baseball would probably be able to diagnose this, except the Rockies are incapable. It's to the point where it's either gross incompetence or they're all going to get nailed for sports betting.

I would literally bet every penny I have that 29 MLB organizations look at predictive models to determine these things. Do I think it's *exactly* the data I used? Probably not, teams have all sorts of proprietary things. But they're using predictive data to look beyond "results". The Cubs traded for Michael Busch despite how poorly he had done at the MLB level, for example. His "results". I would guarantee they looked at his processes from the MiLB and determined whether or not they would translate. I say 29 organizations because I do not know what data the Colorado Rockies use, but it isn't anything good. They're likely the worst run org in professional sports.

At this point? No idea. Last I checked he had a 9 wRC+. It's in like 30 PA's, but at this point, I don't really care.

Ugh. I liked the Ian Stewart when they made that trade.

Hit 96, too.

I responded to someone who's complaint was about his batting average and that he should be dropped in the order. I pointed out his BABIP was low, suggesting that complaining about his batting average was likely misplaced.

Boo. Was too wrapped up in Cubs/Cards and USA/Mexico so had that one on the backburner. Was really hoping we'd see a lot of that pitch after the break as he worked on something new.

I think that's a decent bet for sure. We are probably getting closer and closer to a point where you can buy a team off of those 2-3 weeks.

No, it doesn't mean the "results were good". But doesn't mean Ian Happ isn't and wasn't fine. Listen, if I drive to work, I drive the speed limit, I use my signal, and when I drive through an intersection with a green light, I'm driving fine. If I get plowed into by someone who has a red light, I'm still fine (as a driver, I might have a broken leg). The result is that my car is horsefeathered up, I'm unable to go to work and I have to deal with the police, but I drove just fine. So results are bad, but we know I was fine. Ian Happ is doing everything fine. The results should have been fine. If he continues those processes, much like if I obey speed limits, use signals and observe traffic laws, he will be fine. Bad luck happens. In baseball, with hundreds of hitters who have 600+ instances over 162 games (versus my one driving anecdote) there are bound to be funky data sets within. We have found one with Ian Happ. He's been fine. He will be fine.

Wicks was supposed to follow Pomeranz yesterday, but due to Drew getting knocked out early, they went with Flexen and the plan clearly changed. I actually think Flexen will get the start next time through or they will go BP game. They only need the rotation spot one more time before July 22nd.

I would also posit this, and I don't mean this towards you or anyone; we see a lot of what we want to see. And we remember a lot of what we want to remember. We also tend to remember things that upset us more than we remember other things; it's a lot easier to remember the Ryan Pressly blowup against the Giants than it is a 4-batter-faced appearance against the Pirates where he gave up one hit but struck out two, ya know? Data wise, Happ's fine. PA wise? I think subjective.

No, he is also fine then, too. If he was making a ton of soft contact, if he was chasing a ton, if he was not controlling the strike zone, if his processes were poor, then we can blame him a bit for the .145 BABIP (though no MLB hitter can sustain a BABIP that low). But they weren't. Over the course of 162 games, sometimes the ball goes your way, and sometimes it doesn't. If you're doing the right things and the ball isn't going your way you are fine. Much like if a hitter is doing a lot of things poorly and the ball is just landing...he really isn't doing fine...he's just getting lucky. I'm sorry, I will not agree with this.

Results aren't predictive. Our goal isn't to determine "what Ian Happ is going to do last April 18th" but "what is Ian Happ going to do tomorrow". It's why teams don't function like reactionary fans. We live in the moment, the Cubs live for the next 3 months. Predictive models, expected data, processes, batted ball, BABIP, all of these things suggest he's doing things fine. For example, Ian Happ has a 117 wRC+ over his last 115 PA's. His BA is .177 but has a .145 BABIP. He's running a 10% barrel rate (about career norm), with a 15.7 BB% and a 23.5 K%. It's blatantly obvious that the processes should be around the .340 wOBA we are accustomed to, but a .145 BABIP is unsustainable. He's fine. If he continues to keep these processes, he will be, roughly, the hitter we expect.

What is "lmao" about that? We have plenty of ability to parse data. You're using batting average, but not using things like BABIP and his batted ball data to determine whether it's earned or not. His BA on the season entering the game was .231 compared to his xBA which was .255. That is a .32 point spread. His career BABIP is .308 while his BABIP this year was .274; a .28 point spread. See how close those two things are? His career wOBA is .340 and his xWOBA is .343. Again, notice how close they are? There is plenty of data to support my point here. Please, defend yours more than a dismissing "lmao" and we can discuss it further.