Yesterday, I used my xBABIP equation to identify and discuss eight hitters who appear due for a BABIP surge. Today, I’ll check in on the other side of the ledger, those whose xBABIP marks are significantly below their actuals, suggesting serious downside.
Last year, I utilized our Splits Leaderboard and incorporated shift data into my newest xBABIP equation. So with just a couple of weeks before the all-star break, let’s calculate xBABIP for all hitters and discuss eight of them whose marks are significantly higher than their actual BABIPs, suggesting dramatic upside potential.
Finding hitters on the wire is always challenging. We know scooping someone with a .500 AVG and a bundle of homers over a 2-3 week sample will come back to earth, but how much? Is it their one hot streak for the year or something more viable? I’ve got three surging bats to look at here. One is just north of 50% because I really wanted to talk about him. Deep leaguers will likely only be able to acquire these guys via trade, but we can dive into the backend of the player pool another time.
A few years back, I created a system to help me find under the radar prospects using just position, age at the level, and minor league production (wRC+). I wanted a system besides industry lists to use in dynasty leagues and it worked fine. At the same time though, FanGraphs hired this guy named Chris Mitchel and he created KATOH. His system quickly outperformed mine, so instead of trying to keep up, I asked him to join my fantasy teams. With Chris now gone, my old system is back and running to help find some diamonds in the rough.
As I previously stated, the rankings are just based on age at the level, position, and production. The final value created by the program approximates the players value based on lining up the player to actual prospect grades (80 = MVP, <20 = minor league filler). Obviously, the ranking isn’t close to the final say but I find some hitters before other do.
Note: If any player type seems misplaced, let me know. From eye-balling some values, catchers may be getting too much of a position adjustment.
Fantasy owners tend to give good hitters on bad teams short shrift, and that was certainly the case for Justin Bour this spring. Even though he was coming off a breakout season in which he batted .289 with 25 home runs and 83 RBI in 429 plate appearances, Bour fell to the late rounds in many leagues, lagging behind the less accomplished Greg Bird and Josh Bell in ADP.
Two-and-a-half months into the season, the Marlins first baseman seems to be validating owners’ fears. He ranks 29th in a largely-disappointing pool of first basemen in terms of Roto value (per ESPN’s Player Rater). Bour is batting just .242, and despite posting a .375 OBP, he has scored just 24 runs. With 10 home runs and 27 RBI in 253 plate appearances, he is well behind last season’s pace for both stats. It’s little wonder he is widely available in 12-team mixed leagues.
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Yesterday, I used my xHR/FB rate equation to identify and discuss eight hitters whose marks suggest an imminent surge in their actual HR/FB rates. Today, let’s check in on seven fantasy relevant hitters on the other side of the coin — those whose xHR/FB rates are well below their actual marks, suggesting near-term downside.
In my chat last night, I got several questions on Joey Votto and his power loss. I decided I investigate the drop along with several other regulars who currently have an isolated power (ISO) less than their projected Steam projections.
To get a list of hitters, I took the hitter with a least 150 PA this season and compared their projected and actual ISO’s. Here the top 20.
| Name | Age | Projected | Actual | Difference |
|---|---|---|---|---|
| Chris Davis | 32 | .249 | .079 | .170 |
| Kole Calhoun | 30 | .171 | .035 | .137 |
| Rougned Odor | 24 | .224 | .088 | .135 |
| Giancarlo Stanton | 28 | .367 | .244 | .123 |
| Jay Bruce | 31 | .225 | .109 | .115 |
| Marcell Ozuna | 27 | .227 | .113 | .114 |
| Neil Walker | 32 | .197 | .088 | .109 |
| Domingo Santana | 25 | .211 | .107 | .104 |
| Joey Votto | 34 | .225 | .134 | .092 |
| Addison Russell | 24 | .192 | .102 | .090 |
| Michael Conforto | 25 | .231 | .144 | .087 |
| Yulieski Gurriel | 34 | .182 | .101 | .081 |
| Jackie Bradley Jr. | 28 | .187 | .110 | .076 |
| Rhys Hoskins | 25 | .268 | .191 | .076 |
| Orlando Arcia | 23 | .143 | .067 | .076 |
| Adrian Beltre | 39 | .184 | .109 | .076 |
| Anthony Rizzo | 28 | .261 | .187 | .074 |
| Jose Pirela | 28 | .151 | .078 | .073 |
| Kendrys Morales | 35 | .210 | .138 | .073 |
| Josh Donaldson | 32 | .261 | .190 | .072 |
It’s been a while since I calculated my xHR/FB rate equation and compared its results to each hitter’s actual marks. So let’s discuss eight names, plus two bonus names, with HR/FB rates that fall most short of their xHR/FB rate marks. While there are no guarantees in life, especially baseball, there’s a strong chance that each one of these hitters raises their HR/FB rates the rest of the season, assuming they can maintain the underlying skills driving the marks.
The MLB Draft is unique in that it happens during the season. For the football and basketball drafts, they happen well before the season starts because the players can contribute for the upcoming season. With baseball, the odds are against one single player getting the call this season. That doesn’t mean fantasy owners, especially those in keeper and dynasty formats, shouldn’t possibly be making some moves depending on their needs.
The biggest key for anyone considering rostering a just drafted player, know your league rules. First, some leagues may not allow the drafted players to be rostered until the next offseason draft. Other leagues don’t allow owning a player until they’ve at least played a minor or major league game. In some other leagues, the players are rosterable this next FAAB period. Each one is unique. Let me start the discussion with the last league type.
Batter production can roller coaster up-and-down during a season and many times the player’s production eventually stabilizes at an expected level. But sometimes a hitter intentionally or unintentionally changes his plate approach to achieve a new talent level. I’m going to examine three top hitters, Cody Bellinger, Giancarlo Stanton, and Jose Altuve, and why their struggles are caused by changes in approach.
Over my years of research, I’ve found three main items which point to a true talent change, swinging at pitches out of the strike zone, hitting pitches in the strike zone, and groundball rate (verified with launch angle). When one of these items change, the hitter’s production should also change. Luck could still be a factor in the short run but given enough time, there will be a new output level.
