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Week 1 Statcast standouts

Hard hits, hard throws, and swings getting low, low, low, low.

Kansas City Royals v San Francisco Giants Photo by Thearon W. Henderson/Getty Images

The San Francisco Giants certainly shocked baseball fans this past week with their 13-home run barrage across three games against the White Sox in Chicago and here and there they’ve managed to stir up some surprises on the pitching side, too. A quick glance at stat lines tells some of the story, our game recaps tell some more of the story, like context; and then there’s Statcast, which might very well provide the rest of the narrative.

Now, this post should be considered somewhere between pointless fun and somewhat informative. It’s far too early to draw any conclusions about how the Giants might perform going forward. I like to look at Statcast to confirm what my eyes are seeing and use it as the occasional check on the Giants’ stated beliefs about their players. So, the Giants feel like they’ve put together a lineup of guys who hit the ball hard. They believe they’ve assembled a solid pitching staff. My eyes say this is mostly true. What does the data say?

In the hilariously small sample size of nine games and the first week of the season’s worth of games, does Statcast data support these scouting reports, not just with the lineup but on the pitching side, too? Let’s dive in.

Hitting Heroes

As a team, the Giants are 6th-best in the NL (10th in MLB) in Barrels per plate appearance percentage (6.7%). What is a Barrel?

To be Barreled, a batted ball requires an exit velocity of at least 98 mph. At that speed, balls struck with a launch angle between 26-30 degrees always garner Barreled classification. For every mph over 98, the range of launch angles expands.

That’s basically the measure of a perfect swing on a ball. Is that a skill? Is it luck? Or is a nine-game sample too small to draw any conclusions? I think it is too small for the broader goal I’m working towards here.

Michael Conforto sat out a full calendar year, but the expectations are that he’ll regain his swing and be a formidable threat. Joc Pederson is expected to continue his torrid 2022 line into 2023. J.D. Davis, now fully healed from finger surgery and coming off a season where he registered the best Hard Hit rate in the National League, should be a bopper with David Villar right behind him. The Giants thought that the underlying data showed LaMonte Wade was going to be a force now healthy from a balky knee. Mike Yastrzemski continues to have the team’s support because of the flashes he’s shown. The Giants think they’ve put together a lineup of hard hitters. Let’s look at straightforward Hard Hit rate.

Statcast defines a ‘hard-hit ball’ as one hit with an exit velocity of 95 mph or higher, and a player’s “hard-hit rate” is simply showing the percentage of batted balls that were hit at 95 mph or more.

Here, the Giants are #3 in the NL (44.3%), behind the Dodgers and Cardinals, and #6 in MLB, the Royals, Rays, and Angels also ahead of them. The Giants leaderboard with just the “qualified” hitters (2.1 PA per team game):

  1. Joc Pederson - 60% (16th in MLB)
  2. J.D. Davis - 58.8% (23rd in MLB)
  3. LaMonte Wade, Jr. - 52.9% (38th in MLB)
  4. David Villar - 50.0% (46th in MLB)
  5. Michael Conforto - 50.0% (48th in MLB)
  6. Blake Sabol - 50.0% (55th in MLB)
  7. Mike Yastrzemski - 41.7% (119th in MLB)
  8. Brandon Crawford - 40.0% (134 in MLB)
  9. Wilmer Flores - 30.8% (211 in MLB)
  10. Thairo Estrada - 24.0% (250 out of 274 in MLB)

That’s pretty good. Half the lineup is in the top 20% of the league so far. The week featured some impressive things like both LaMonte Wade Jr. and David Villar setting new exit velocity records for their careers:

111.5 mph for Wade Jr. on this splash hit:

106.8 mph for David Villar on his first grand slam:

And then there was Mike Yastrzemski, who tied a previous high in Statcast EV with this 109.7 mph home run. The White Sox comment? “That ball is absolutely vaporized...”

And if we’re just talking raw distance, Blake Sabol’s first career home run was the 25th-longest ball hit in the opening week of the 2023 season - 434 feet

And just to circle back to Michael Conforto — he hit the go-ahead home run in yesterday’s game, and on the week, he’s in the 94th percentile in average exit velocity, 77th in max exit velocity, 79th percentile in Hard Hit rate, 72nd, 73rd, and 76th in expected slugging, Barrel rate, and expected weighted on base average (xwOBA), respectively. Not bad for a guy who missed a year from shoulder surgery.

Pitching Paragons

It wouldn’t surprise you if I told you Statcast rated Gerrit Cole’s 4-seam fastball as the most valuable pitch through week one of the season, with an incredible -5 in run value. Broadly, that means his fastball was so impactful on a pitch-by-pitch basis, given runners on base, outs, ball and strike count, that through just two starts (12.1 IP), it’s prevented — theoretically — five runs. Presuming 10 runs in Statcast is the same as 10 runs at Baseball Prospectus and FanGraphs — as in, 10 runs = 1 win — then Cole’s fastball has been worth almost half a win.

I say all that to contextualize the -2 run value Sean Manaea netted with his changeup this past week. Meanwhile, Statcast LOVES Anthony DeSclafani’s and Sean Hjelle’s week one sinkers and was fine with Alex Cobb’s, but it wasn’t a fan of Sean Manaea’s and felt Logan Webb’s was stinky poo-poo.

Webb did well with his slider (-1), but DeSclafani was a little bit better with his (-2). On the other end of the spectrum, Ross Stripling’s was simply putrid (+3).

Ross Stripling’s dreadful week — in just 6.2 innings of work, FanGraphs said he generated -0.4 wins above replacement — led to this very funny (in a sad way!) tweet and quote tweet:


Now, Stripling wasn’t the absolute worst pitcher out there this week, which seems surprising! Taylor Rogers faced twelve batters, ten balls were put in play, and the expected weighted on base average was .541. Stripling’s was .487 and Manaea’s was .407.

For as rough as Logan Webb’s results were, it seems almost completely driven by the limits on shifting. His .267 xwOBA (which, again, is quality of contact plus strikeouts plus walks), was fourth-best on the team (behind Scott Alexander, John Brebbia, and Anthony DeSclafani). Scaled to starting pitchers, he and DeSclafani (.251 xwOBA) were in the top 20 (DeSclafani at #12, Webb at #17).

Right away, I think both the pitching and hitting Statcast numbers speak to what the Giants have been saying all offseason about the players on their roster. The mashers can mash and the pitching staff can be effective, top to bottom. These terrible outliers could be the result of small sample size shenanigans — Stripling and Webb might have to change their sequencing or pitching plans against certain hitters because of the clear effects the shift limits are having on their results — but we’ll just have to wait and see.