The All-Star game has come and gone, but the festivities are ongoing here at RotoGraphs. It’s time to rank the first half’s “All-Sell-High Team.” These are players who had big first halves, but who aren’t necessarily the best bets to repeat that performance in the second half. Without further ado, let’s get right to the list: Read the rest of this entry »
Contrary to popular belief, the secret to rebuilding (and winning) your fantasy league is not hoarding prospects. This season, you could be waiting patiently for the arrivals of Michael Kopech, Willie Calhoun, and Luis Urias to save your team, or you could have jumped on pop-up producers like Max Muncy, Jesus Aguilar, and Ross Stripling. Last year, Aaron Judge, Luis Severino, and Charlie Morton were universally available if your timing was right.
The thing about prospects is that sometimes they pan out, and sometimes they don’t. Even a “successful” one like Ronald Acuña has just a 114 wRC+, with a rest-of-season projection slightly below that. In real life, that’s fantastic for a 20-year-old and Acuña is a likely future star. But in the meantime his production is nothing special.
And again: Acuña is a success story. Owners might wait years for the likes of Byron Buxton, Dansby Swanson, and Alex Reyes to carry their teams to relevancy. All the while, players like the following four who are owned in less than 40 percent (well, actually, 43 percent) of Ottoneu leagues have been quietly carrying contenders: Read the rest of this entry »
As we push toward the All-Star break, it’s time to look at young arms and how their innings are tracking. I used last year’s total plus 25% for a rough estimate of what teams might be looking to use as their bar for a guy who they want to limit. Now just they because they might have enough innings “available” based on this calculation doesn’t mean the team won’t still look to limit them if they have health concerns. I think it’s fair to say that if they have about 85 innings or so left in the tank, then overwork won’t be a driving force behind limiting a pitcher in the second half.
A couple weekends ago, Dave Appelman asked my fellow writers and me what features we’d like to see available at RotoGraphs (more additions are in the works) and a FAAB (free agent acquisition budget) bid estimator was discussed. With so many leagues and so many bidding setups, I accepted the daunting challenge. I’m beginning to produce some limited usable results.
Before I go into the many inputs in FAAB bids such as declining budgets and absentee owners, I needed:
1. A way to measure owner seniment before the normal Sunday FAAB bids.
2. A reliable source of FAAB bids.
For the first source, I’d like to thank fellow RotoGraphs contributor, Al Melchior for pointing out that CBS Sportsline displays historic weekly ownership rates. Every host website will display ownership rates. What was important with this source is they have a ton of quick grab waiver wire leagues. As soon as a player bursts on the scene, owners can go pick them up off the wire. The ownership rates for these hot commodities immediately begin ticking up. These values are available but the bases need rounding a few times to collect them.
Yesterday, I discussed the seven players whose ownership rate jumped the most in CBS leagues. Today, I’m going to check in on the dropped players. I often find opportunity here a pitchers coming off one bad start get jettisoned or a hitter in a cold spell are kicked to the curb. The dropped list is a bit tougher to analyze, though, as many of them were bitten by the injury bug and placed on the DL, or demoted to the minors. So I’m only going to include those that are healthy and remain in the Majors.
I’m going to blame Mark Melancon. I started out yesterday with the hope of writing about him. The article was selfish because I took a chance on Hunter Strickland before he was named the closer and my gamble paid off. With Melancon back, I wanted to see if his reduced velocity cutter would still be useful. And that was as far as I got with the article.
I was sick of thinking about fantasy baseball. The problem is that when your livelihood requires continuous fantasy baseball content, this sickness can’t last. I tried to move onto another topic with no luck. After a few unproductive hours, mainly wasted on Twitter discussing valuing player risk, I just gave up. The dog days of summer hit me head on and I lost.
This event usually occurs me a couple times during the summer with content and demands coming at me constantly. I approach them two ways. Either I just power on and produce 20-grade material or beg my bosses for a break. As this article demonstrates, I am going with the first approach.
There are, like, a dozen articles of this nature written daily — that is, “buy-low” candidates using some kind of xMetric, likely derived from Statcast. That’s fine. I’m not hating on it. This was my modus operandi when I first started writing at RotoGraphs, and it’s how I really started to understand the cyclicality of player performance and the differences between descriptive and predictive metrics.
Speaking of which, I have no desire to rehash the “what xwOBA should really represent” discussion that consumed the sabermetric sphere a week or two ago. (Although, for reference, I’ll link you to Baseball Prospectus, MLBAM’s Tom Tango, and FanGraphs’ Craig Edwards.) Primarily, I want to provide some facts about xwOBA followed by some non-facts about how I use xwOBA to keep my biases in check.
There are two important tenets to xwOBAism. At the player level, wOBA does not always converge on xwOBA…
The phrase “Buying Low” gets thrown around in the baseball community. I’m not sure if owners can actually buy low on many of these frustrating but talented players. Owners need to be willing to sell. I going to try to redefine the concept of buying low concentrating on drop rates and go over a few potential targets.
When I hear or read about buying low on a player, the touts are focusing on buying a good player during a cold streak. Paul Goldschmidt fits this label with his .208/.324/.380 slash line. Owners paid first round prices for replacement level production. But are Goldschmidt’s owners selling low? Probably not.
Going over some recent trades at the Yahoo trade tracker, Goldschmidt is being traded straight up for players such as Clayton Kershaw, Joey Votto, Patrick Corbin, and Shohei Ohtani.
His value is down some (and should be with the K% spike) but not horribly. He’s still owned in 99%+ of leagues at ESPN, Yahoo, Fantrax, and CBS. Even the most frustrated owners in shallow leagues aren’t moving on. So why should owners focus their time and energy on players who even the most frustrated owners aren’t moving on with?
Rarely is OPS (on-base percentage plus slugging percentage) a fantasy stat. It’s off many people’s radar but it’s widely available and closely mimics a position player’s overall hitting talent. While other stats (e.g. wOBA and wRC+) also give a hitter an overall value, these stats aren’t available at every website. Most sites have their own unique blend but OPS is commonly available. Because of this availability, I’ve been using it as a baseline in recent articles on adjusting projections based on prospect pedigree and when hitters get platooned ($$). Now, it’s time to use OPS to help predict the individual categories.
The process I used for this study was to simply see how much various stats changed when OPS changed a certain amount. For rate stats (e.g. batting average) the conversion is straightforward. For counting categories, I put the stats on a per 600 plate appearance scale. Additionally, I only compared data from 2015 to 2017 during the current “juiced” ball era. I know the process is not close to being 100% precise and that is fine. I’m just trying to create general adjustments and can look to hone the process later. I’m putting in 20% effort to get 80% of the answer.
My current aim in fantasy baseball is to find instances where player evaluations can be improved. With several prospects recently getting called up, I am trying to answer the simple question: is there any projection information to be gained from being a highly touted prospect. The short answer is yes, but it took me a while to get good results.
I wanted to keep the analysis simple so I used all available Steamer projections which to back to 2010. Additionally, I used Baseball America’s top 100 ranked prospects for that time frame. From these two data sets, I compared the hitter’s projected results to the actual results for their first few seasons.
