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Two players that come to mind right now are Kevin Gausman and Jeff Hoffman. Are these guys washed? Are they broken? It’s somewhat reasonable to think they might be. Gausman is old in baseball years (35 years old), so his peak is definitely behind him. And he has 4.38 ERA for this season while his K-rate is down below 9 K/9 (he is currently at 8.98 K/9, so just barely below). His BB% is creeping up, and his K-BB% is slowly declining. Hoffman, for his part, has been a near disaster at times this season, to the point you might be surprised to know his ERA is only 3.94. He lost the closer gig in Toronto to Louis Varland, and it’s hard to forget him giving up a tying homer in game 7 of the World Series to noted slugger Miguel Rojas (who has 60 career HRs in over 4,300 career PAs, which would be an average of just under 9 HR per 650 PA.

Please, blog, may I have some more?

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A recent case in point is Jake Bennett, pitcher for the Boston Red Sox. He is undoubtedly off to a great start to his MLB career, as he’s put together 59.1 innings of a 2.58 ERA and a 0.94 WHIP. He’s also collected 6 wins, which is fantasy gold but also probably more the result of the recent Red Sox hot streak than it is a stat that gives us an idea what to predict moving forward. But when readers and friends have asked me what I’ve thought of him, I’ve had to basically shrug my shoulders and say that I wasn’t sure yet.

Please, blog, may I have some more?

For me, one of the most challenging things about fantasy is when I see things that others I respect in the game apparently don’t. For instance, if I’m in on a player while no one else seems to be, that makes me extremely anxious. Anytime there’s a FAAB run and I go spend a hefty chunk on a guy while the back-up bids for him are virtually nonexistent, I question myself. A lot. Anytime I roster a guy on as many of my teams as I can, then I check rostership percentages to see that he’s rostered in basically no other leagues, I question myself. A lot. In both cases, I start wondering: Option A – Did I see something everyone else didn’t? Option B – Or do I think I’m seeing something good that isn’t there?

Please, blog, may I have some more?

I may have mentioned once or twice by now: Fantasy is a game a failure. We cannot predict human behavior 100% of the time, so our predictions about players are going to be wrong. Often. The best fantasy players aren’t necessarily good at predicting what players will do; they are simply less bad at it than the rest of us are. The best fantasy players are also likely less reactive to their analytical misses, able to respond and adjust accordingly, while the rest of us are still yelling at ourselves for our misses – or, even worse, blaming players for how they have failed us. The best fantasy players are able to acknowledge their analysis was wrong and quickly begin the process of rebuilding analysis to help moving forward. 

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This season’s line for Valdez is enough to inspire a rage drop: in 67.2 IP, he has damaged his fantasy managers by earning a 4.39 ERA (supported by a 4.34 xERA, 4.14 FIP, and 4.29 xFIP) and a 1.32 WHIP. His BB/9 is up to 3.33, not great. His K/9 is down to 7.18, also not great. His K% makes things look even worse, as he’s down to 18.3% from last year’s 23.3%, causing his K-BB% to drop from last year’s 14.8% to 9.8% in 2026.

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Usually, that means I’ve picked out player options to turn to in case disaster strikes – which when it comes to pitching means I have a group of guys I can turn to for K help if any of my big guys go down. Well, my big guys are going down, so here are two players I’ve been paying attention to that are starting to pay dividends for my teams. Maybe they can pay dividends for you as well. One is for shallow league consideration while the other is for our deep league players, and coincidentally they are both Houston Astros.

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This week, I attempt to turn a disinterested eye to Garrett Crochet. In my drafts, I often found myself picking between 11 and 15, meaning that my player choices once my pick came up usually included hitters like Vladimir Guerrero Jr., Kyle Tucker, and Francisco Lindor. I’m high on all 3 of those guys, so I was happy to choose one of them. But I had a late pick in many of my drafts, well over 50% of the leagues I’m in, so I didn’t feel like I should draft the same guys every time. That led me to look more seriously at late RD1 pitchers than I have in the past, and Crochet was the stud pitcher most often available in the late 1st. Let’s just say I have a number of Crochet shares. And that hasn’t been great to start the season, as the pitcher I expected to be so good has been anything but.

Please, blog, may I have some more?

Happy Monday, Razzball faithful! It’s your favorite patriarchal pal, MarmosDad, back for another edition of Monday madness. The good news? I’m here! (hopefully, that’s some good news). The bad news? Today won’t be an update of the Top 100 Starting Pitchers. Grey asked us to save that for Wednesday’s open slot. On Wednesday, I’ll have […]

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Anyone else out there have a theme song when they draft their baseball teams?

I draft hard (he drafts hard) every day of my life
I draft ’til I ache in my bones
At the end (at the end of the day)
I take home my hard-earned team all on my own
I get down on my knees
And I start to pray
‘Til the tears run down from my eyes
Lord, somebody (somebody), ooh somebody
Can anybody find me… ADP to love?

Just me? Alright.

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Last week, I introduced the goal of this series: utilizing data visualization to try and narrow in on fantasy baseball insights. We looked at ERA across the draft, finding some potential values based on ADP. Today, we’ll take a closer look at Starting Pitcher WHIP by ADP.

To begin with, what’s the context in which we should gauge whether an SP’s WHIP actually helps our team? Here are WHIP trends over the last 5 years:

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There is a LOT of information available for fantasy owners to try and digest these days. New writers and podcasts emerge every day (over 500 different fantasy analysts by last count). New stats and ways of slicing and dicing existing data are constantly emerging. Don’t get me wrong – I love the latest Statcast research as much as the next guy. But fantasy writers often pile up the acronyms and exotic statistics, as if 2000 words on spin rate has inherent interest just because it’s in-depth. It can be hard to find actionable fantasy moves in a table with 10 varying components of xStats.

I’m kicking off a new series today, utilizing data visualization to try and narrow in on fantasy baseball insights. Good visualization helps you achieve your goals by channeling success onto your subconscious until your reality lines up with your drea….I’ve been watching too much late-night Tony Robbins. Good data visualization takes complex raw data and translates it into easily-understood, actionable images.

Please, blog, may I have some more?