2018 Pod Projections: Tommy Pham

The 2018 Pod Projections are now available! For the first time, the package includes NFBC ADP, along with all historical Pod-developed xMetrics. My projections are based on the methodology shared in my eBook Projecting X 2.0, and the process continues to evolve and improve (thanks Statcast!).

2018 Pod Projections Index:
Shohei Ohtani

There’s no doubt that Tommy Pham won leagues last year. He headed into the 2017 season as a minor leaguer with just 358 MLB plate appearances since 2014 and didn’t make his Cardinals season debut until early May. He then proceeded to wOBA .398 and go 20/20, while batting over .300…at age 29. Whaaaaaat?! The out of nowhere performance composed of all-around contributions have not surprisingly excited fantasy owners. If you filter NFBC ADP by drafts that have taken place only in 2018, he’s the 57th ranked player overall with an ADP of 58.2. Shockingly, fantasy owners seem in consensus that he’s for real, as the difference between his Min Pick and Max Pick is only 57 (31 to 88), which is less than the majority of the players surrounding him in ADP.

He’s now assured a starting outfield job, so let’s find out whether the Pod Projections validate the hoopla or question his ability to come anywhere close to a repeat.

Plate Appearances: 612

Pham figures to open the season as the Cardinals number two hitter, which means that if he remains there all season, he’ll earn the second highest number of plate appearances. Normally, an every day second place hitter would come to the plate more than 612 times. However, Pham is no veteran and I built in some risk of him flopping and losing his job, or at the very least, getting dropped in the order.

BB%: 12.1%

Pham has always posted strong walk rates in the minors and that translated during his first nearly full season in the Majors. His Plate Discipline metrics fully supported his 2017 walk rate, as both his O-Swing% and Swing% were significantly below the league average. Fewer swings, especially at pitches outside the strike zone, should lead to a higher walk rate. You have to assume some degree of regression off 2017, but his patience is for real.

K%: 21.8%

I finally brought back my hitter xK%, which for some reason, I abandoned years ago and never really used. I have no idea, because the equation is darn good! Pham’s strikeout rates in the minors generally sat between 20% and 22%, and his 2017 MLB mark fit right in. However, his xK% was actually a slightly more impressive 20.1%, suggesting a bit of upside from his 2017 mark. I am forecasting just some of that upside is realized, acknowledging the chance that pitchers adjust to the new kid on the block.

GB%/LD%/FB%: 49% / 21% / 30%

For a guy who has been showing immense power, it’s surprising that Pham managed to post just a 26.1% fly ball rate in 2017. He actually hasn’t gotten his FB% above 29.5% during any of his MLB stints, resulting in a career average of just 27%. So why on Earth would I forecast a jump to 30%? Well, because his minor league marks were typically much higher, and the MLB average sat at 35.5%. So this is a combination of regression toward league average and accounting for his higher minor league marks.

BABIP: .335

It wasn’t just speed and power on display when Pham was in the batter’s box. He also posted an inflated .368 BABIP and showed strong BABIP skills to boot. His xBABIP was a robust .348, thanks to excellent components across the board driving the equation. Obviously, some regression needs to figure into the mix, but he’s a legit high-BABIPer.

HR/FB Ratio: 18%

Wowzers, while Pham did post a crazy 34.6% HR/FB rate in 2016, it came in just 159 at-bats. While regression manifested in 2017, he still maintained a big rate at 26.7%. Both these marks were significantly higher than his minor league days in which he typically posted marks in the low-to-mid teens. And Busch Stadium is no right-handed power inflating park! But here’s the thing — his xHR/FB rate was 27.4% in 2016 and 22.5% in 2017. Sure, these marks are lower than his actual, but still, TOMMY PHAM is right up there with the big boys and was fully deserving of HR/FB rates above 20%. Who saw that coming?!

Now now, he’s entering his age 30 season, his minor league track record is far less power-filled, and he’s got just 758 MLB at-bats to his name with his career 25.9% HR/FB rate. Clearly, the right call from a projection standpoint is to forecast regression, and below his 2017 xHR/FB rate because you have to think the skills driving that mark are at greater risk for a decline than an increase or even remaining stable.

Runs and RBI: 92 and 68

The Cardinals should have a solid enough offense and the two-hole is a respectable spot to accumulate runs plus runs batted in. Pham was far more amazing at scoring runs and knocking in runners than we would have expected in 2017, so I’m expecting those rates to regress. Still, 160 R + RBI are strong for the second hitter in a lineup.

SB: 22

One of the primary reasons we’re all so intrigued by Pham’s fantasy potential is that he has a stolen base cushion to lean on. Though he hadn’t shown a real willingness to steal bases in the Majors until 2017, he always had in the minors. With a good Spd score and solid enough success rate, only age is driving a small reduction in steals.

Below is my final projected hitting line, along with the other systems for comparison:

Tommy Pham 2018 Projections
Pod 612 527 0.279 21 92 68 22 12.1% 21.8% 0.335
Steamer 753 494 0.267 19 78 66 18 11.3% 25.0% 0.336
Fans (33) 628 539 0.284 22 104 89 26 12.7% 21.8% 0.342
ZiPS 532 463 0.263 20 78 68 18 11.1% 24.1% 0.322
ATC 571 488 0.276 23 92 74 22 12.6% 25.4% 0.346

Isn’t it amazing when even for someone with such limited MLB experience, the systems are still relatively close in category forecasts?

Not surprisingly, the Fans are most bullish, projecting the most at-bats, highest batting average, most homers, runs scored, runs batted in, and steals. I’m actually second highest in batting average and it’s not even because of the use of my xBABIP equation. Instead, it was using my xK% equation which led to a strikeout rate projected that is tied for lowest. All other systems are 24.1% or higher, which is a significant difference. It’s rather interesting that despite the difference in strikeout rate, Steamer, ZiPS and ATC still all project similar home run totals and batting average.

So bringing everything back to the beginning, it appears that the Pod Projections do in fact validate all the hoopla. It’s always a challenge figuring out what to do about late age breakouts like Pham, but fantasy owners don’t seem to be the least bit hesitant here. Given the regression baked in to my projections, it’s also very possible he outperforms. I’m a phan.

We hoped you liked reading 2018 Pod Projections: Tommy Pham by Mike Podhorzer!

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Mike Podhorzer is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year. He produces player projections using his own forecasting system and is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. His projections helped him win the inaugural 2013 Tout Wars mixed draft league. Follow Mike on Twitter @MikePodhorzer and contact him via email.

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Jim Melichar
Jim Melichar

Came to the same conclusions on Pham after a deep dive a couple weeks ago. I like that he studies his own batted ball data. I especially dig the power to all fields.

I came to the opinion that the only real risk lied in K% collapse and other normal age related risk.