Science and Baseball

Month: October 2016

Using the Stuff Metric for Scouting the Arizona Fall League

Believe it or not, the Arizona Fall League is a place where players other than Tim Tebow go, to refine their skills before making it to the bigs. When they aren’t faith healing fans who have fallen ill, AFL pitchers are throwing a repertoire of pitches that they hope will propel them to the next levels of their minor league careers. Luckily for us, MLB has put out the pitchf/x data from the past 2 seasons (with the 2016 data coming). This allows me to calculate pitcher’s Stuff from the AFL.

The Stuff metric has been closely related to a lot of performance metrics at the MLB level – but I have not had a chance to look at any minor league data, until this point. I wanted to see how Stuff in the AFL compared to MLB Stuff – and to see if this has any potential as a scouting metric in parks that have PitchF/X. Let’s compare.


I used the calculated Stuff metric from the 2016 as my MLB standard. The stuff list is the same one found on I downloaded the PitchF/X outputs from Baseball Savant (for the 2014, and 2015 AFL seasons), and calculated Stuff in the same way mentioned here. To try and get some sort of consistency, I only calculated stuff for pitchers that threw 30 pitches in the AFL. Additionally, pitchers had to have thrown at least 10 innings in the MLB in 2016. For analysis, I compared the 2016 Stuff against the AFL stuff using a Pearson’s correlation coefficient.


First off, from the 116 different pitchers that had PitchF/X data in the AFL, only 23 managed to fit both inclusion criteria. The average fastball velocity, offspeed velocity, change of speed, and break distances, as well as correlation coefficients can be found in table 1.

Table 1. Summary of variables from AFL and MLB.

Stuff FB Velocity Offspeed Velocity Change Movement
AFL 0.31 ± 0.91 92.54 ± 3.07 81.38 ± 4.77 0.12 ± 0.04 9.65 ± 6.06
MLB 0.73 ± 0.84 93.37 ± 3.33 81.18 ± 3.65 0.13 ± 0.03 13.74 ± 4.12
r 0.59 0.85 0.67 0.5 0.33
r2 0.35 0.72 0.44 0.25 0.11


All components of the Stuff metric correlated well between AFL and MLB measures. Velocity had the strongest relationship (r = 0.85) between the measures at the AFL and MLB. Movement had the weakest relationship (r = 0.33). Overall, AFL stuff accounted for 35% of the variance in MLB stuff. Not great, but definitely a good start. This is really a small sample size, and if we omit the data from one outling pitcher (Adam Morgan), the value goes up to 0.77.


The PitchF/X system can be a bit finicky, so there’s a chance that some of the movement data discrepancies are a factor of the different parks in the AFL. Maybe these cameras weren’t as sensitive to the pitch movement, or maybe, the pitchers at this time in their development, weren’t as good at generating movement.

Here are the top 15’s for the 2014, and 2015 AFL’s

2014-afl-leaders 2015-afl-leaders

In summary – there is a decent relationship between AFL and MLB Stuff – it isn’t perfect, but this could be used as a possible way to track pitcher development, and another tool for evaluating Stuff prior to arriving in the MLB. Right now, there aren’t enough pitchers from the AFL who have made their way to the MLB to truly get an idea of how their Stuff develops – but this is an encouraging start.

Now, if we can just go back to watching more Tebow…


The 2016 Stuffies! – Rookies of the Year

Ladies and gentlemen, put on your finest tuxedo, and get “Golden Globe” drunk – it’s time for the culmination of a year’s worth of Stuff reports – The Stuffies! While the Stuffies currently have less cache than some of baseball’s more talked about awards – like the MVP, there’s no room for philosophizing about what “valuable” means. Like a Mark Shapiro-led front office, these awards are data driven. Here are the BBSWAA (Baseball Stuffies Writers’ Association of America) we’ve taken the time to breakdown Stuffy Awards into Starting and Relieving categories.  There won’t be any funny business where we pit a 60-inning reliever against a 200-inning starter.

In the trend of having awards shows with great hosts; the Billy Crystals, and Neil Patrick Harrises of the world, the Stuffies would like to welcome Nick Dika to provide his insight into the MLB’s most (and least) Stuffiest performances.


The Stuffies will consist of awards for:

Rookie of the Year Stuff – Starter

Rookie of the Year Stuff – Reliever

Best Starting Rotation Stuff

Best Bullpen Stuff

Top Reliever Stuff

Top Starter Stuff

We’ll also present the “Not-so-Stuffies” for the pitcher who, despite lacking in the Stuff department, still managed to churn out innings on the season.


To have the best Stuff – it isn’t about catching lightning in a bottle. You can’t just show up one day, throw the lights out, and claim you had the best Stuff in the MLB. That’s just not how the world works! To be eligible for the Stuff awards, I wanted those in the top 25% of innings pitched on the season, for both starting pitchers and relievers. This meant pitching 156 innings for Starting pitchers, and 46.1 innings for relievers. For rookies, those numbers were 63 innings for starters, and 24 innings for relievers.

The Stuff metric is unfair to knuckleball pitchers, so they were removed from the analysis.

Team Calculations

To calculate the best Stuff on starting staffs and bullpens, the innings weighted stuff was calculated. Each pitcher’s stuff was normalized to their total contribution to innings for their team, then added together to get one Stuff value for each rotation and bullpen. This produced our Stuff champions.

And without further adieu, let’s begin… the 2016 Stuffies!

Rookie Relievers

Brian Ellington

The big E as they call him down in Miami, put up great numbers in his rookie season. His sub 3 ERA matched up well with his 97mph fastball. Perhaps Jeffrey Loria will build a nasty stuff statue in centerfield at Marlins park to honour this historic performance? Despite his awesome stuff, Easy E struggled with his command at times.

Matt Bush

With the Silver Stuffy, we have Matt Bush. Matt Bush is featured prominently in the Stuffy awards – and if you watched Game 3 of the ALDS, you already know why. He has nasty, nasty Stuff. His fastball can get up into triple digits, and he separates his pitched by nearly 18″. That’s a lot of ground to cover at a high speed.


Mauricio Cabrera 

Here at the Stuffies we don’t discriminate against small market, west coast or non-contending teams when we hand out our hardware. And that’s why Mauricio Cabrera is taking home a Stuffy this season. If you don’t recognize his name you will soon. Pitching for the retooling Braves means you’ll know him as “the top reliever available at the 2017 trade deadline”

Rookie Starters

Dylan Bundy

While it’s a bit later in his career than we may have predicted, Dylan Bundy takes home a bronze Stuffy for Rookie Starter. Bundy’s combination of electric stuff and pitching for the Orioles means that he will almost undoubtedly turn into an ace when he is traded to a different team for spare parts at some point in the future. That or he will sit unused in the Bullpen while division rivals deposit baseballs in the outfield bleachers, eliminating them from the playoffs.

Kenta Maeda

Kenta Maeda has the lowest velocity of anyone on the Stuff lists, but he has elite separation between his pitches, and his change in velocity is close to the top of all of the MLB. This is a pretty impressive rookie performance for a command type pitcher.

Jon Gray

Finally, Jon Gray takes home the Gold Medal for Rookies! Grey had an elite fastball, and paired that with elite change in speed, and above average pitch separation. He had a great season for the Rockies – which amounts to a super amazing awesome season for a pitcher anywhere else. His beard is already elite, but now he’s the Stuff rookie of the year. Congrats, Jon Gray!

*** break for commercial music starts playing ***

So, a huge congratulations go out to Jon Gray and Mauricio Cabrera. You both had great rookie seasons, and showed the MLB what your Stuff was made of. Next season, maybe your team might give you a hand and you can win some games.

When the Stuffies return – let’s look at what starting rotations and bullpens had the best Stuff of the season! Stay tuned for musical performances from the Thrill of Agony, and the Wet Wingsmen.

I HAD concerns about Marcus Stroman’s workload

A lot has been made about Aaron Sanchez’s workload this season. He’s entering uncharted waters for innings pitched, throws incredibly hard, and is insanely awesome. Little has been made about the workload Marcus Stroman has endured this season – where he just crossed the 200 inning threshold. Remember when he and Sanchez were yelling about 200 innings in the off season? It’s awesome to see their hard work rewarded this season.

Given the ACL injury Stroman sustained last season, a lot of his workload occurred behind the scenes under the watchful eye of Blue Jays’ physiotherapist Nikki Huffman (at the time, from Duke University). He only pitched 27 regular season innings in 2015 with the big league team. Despite the baseball reference page saying he had a limited workload for innings, he was without a doubt, using his arm. When Stroman first came up in 2014, he was used as a reliever, before getting his chance to start. This once again, limited his innings. I wanted to use Fatigue Units to examine changes in Marcus Stroman’s workload over the course of his professional career, and see if 2016 was a giant spike that could lead to future injury.

First of all, I had to take a few liberties with the data set. For minor league data, there are no values for pace, starting vs. relief innings, or total pitches. So, I had to make some changes. I once again used a linear regression approach, and tried to find out predictors for pitch counts in a season – using MLB data. I included games, games started, innings pitched, BB/9, and K/9 as input variables – all which ended up being significant predictors. Overall, this model produced an R2 of 0.98, with a standard error of 131 pitches. It isn’t perfect, but it will do for this application. estimated-pitches

The equation for predicting pitches from MiLB data is:

Pitches = -1.72 + 2.41 * K/9 + 0.62 * BB/9 + 15.60 * Games + 81.45 * Games Started

So, we’re now one step closer to calculating FUs. For the remaining information, I used the average fastball velocity from the MLB data, and the pace from the MLB data. I assumed there was greater care given to the type of pitching appearances (for example, how Sanchez’s MiLB starts were short in duration, but still 5 days apart). I made the assumption that all innings were starter innings, and used these for the calculation of MiLB FU’s. As a reminder, I am using “Predicted FU’s” from FanGraphs data – not the actual calculated FUs, so there can be an error of up to 3.5 FU’s. For a refresher – read up here.

Marcus Stroman Workloads


Without a doubt, 2016 is the highest traditional workload season that Stroman has seen. He has set career highs for pitches, and for innings. Compared to 2014 (his next highest season), 2016 represents a 23% increase in innings, and a 45% increase in the total number of pitches thrown.

Now, looking at FU’s, the story is not nearly as daunting.


His highest workload season before 2016 saw Marcus accumulate and estimated 32.6 FUs, where as he sits at 33.9 FUs in 2016. This only represents a 4% increase in peak workload. This is because in 2014, Stroman pitched more innings out of the bullpen, and in 2016, he works solely as a starter. As I had previously written – typically, someone who throws out of the bullpen throws at a higher effort level than when they are a starter. This is the same for Stroman – 95mph when he worked in relief with the Jays in 2014, compared to 93.5 when he worked as a starter in the same year.


Traditional workload metrics (innings pitched, and pitch counts) have long been researched, and the findings have all come back as being null – these metrics don’t help in injury prevention or prediction. Even less can be said about Fatigue Units – because there has been next to no research on this topic – other than what you have read on this website! That being said, this shows a very encouraging trend – that Stroman’s workload has been closely monitored by the Blue Jays staff, and he is not showing any signs of breaking down.

I once HAD concerns about Stroman’s workload increase, but I am comfortable in saying that those concerns have been alleviated.


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