I’ve recently written a couple of columns sketching a general measure of outfield fielding by looking at putouts the outfield turns as a percentage of team fly balls, using 2002 season data.

What about unit defense in the infield, though? Can we do the same thing there, except with ground balls instead of flies? And can that lead us to some really strange conclusions?

Yes on all counts, with some problems. While outfield putouts are context-neutral–each time a putout is recorded the batter, and only the batter, is out–infield putouts are context-heavy. A man on first means a successfully turned ground ball to short goes to the second baseman for the first out, and then (if possible) a second putout is recorded by the first baseman if the ball arrives there in time to get the batter.

For my purposes, though, I’m only interested when the infield turns any out, and only that first out. I’m going to try and isolate that by looking at infield unit POs by making a few adjustments:

  • Catcher POs, which normally include pitching staff Ks, have pitcher Ks removed.

  • IF unit POs have number of DPs removed so they’re not rewarded for playing behind bad staffs that put a ton of guys on base.

  • IF unit POs do not account for SB/CS, PO on OF assists, and related miscellaneous events.

So whenever I talk about IF POs from here on, remember it’s not raw, it’s adjusted.

Now, because infielders snag a lot of putouts on line drives, this is going to be a little shocking at first.

       Ground  Adjusted  IF    
Team   Balls    IF PO   PO/GB  GB/tFB
Dbacks  1968    1961    100%    1.41
Expos   2143    2151    100%    1.61
Indians 2024    2032    100%    1.44
Padres  2012    2053    102%    1.53
Orioles 2119    2171    102%    1.50
Rockies 2108    2164    103%    1.53
Reds    2108    2177    103%    1.51
Jays    2035    2106    103%    1.37
Tigers  2089    2179    104%    1.30
Pirates 2166    2265    105%    1.68
A's     2128    2233    105%    1.43
Rangers 1982    2091    105%    1.37
Royals  2067    2181    106%    1.42
Astros  1940    2075    107%    1.38
Braves  1977    2132    108%    1.40
Giants  1875    2034    108%    1.19
Cubs    1753    1903    109%    1.31
Phils   2028    2202    109%    1.55
Cards   1935    2104    109%    1.36
Mets    1887    2060    109%    1.27
Yankees 1907    2089    110%    1.26
M's     1809    1982    110%    1.09
Red Sox 1976    2167    110%    1.46
DRays   1853    2041    110%    1.10
Brewers 1866    2059    110%    1.30
Angels  1854    2051    111%    1.22
ChiSox  1892    2105    111%    1.25
Marlins 1861    2083    112%    1.26
Dodgers 1856    2111    114%    1.33
Twins   1737    1994    115%    1.00

The average team saw 1,965 ground balls, and got 2,227 adjusted putouts from their infield unit, for an average rate of 107%. The GB-FB ratio here is actually playable balls as (ground balls/[fly balls-HR]), instead of the published one, and the average adjusted GB/FB ratio is 1.36. Anyone who wants to send me detailed distributions of line-drive and fly-ball outs among fielders can drop me a line and I’ll start working on some seriously cool stuff.

That’s an interesting table, no matter how you look at it. While the outfield distributions clustered within 12%, there’s about a 15% spread in the ability of the best-fielding infields to turn their share of playable balls into outs. And the Twins (led, as we’ve seen before, by Corey Koskie), would seem to have a league-best infield unit to go with (by PO/FB, anyway) a league-bottom outfield.

The problem with infield defenses is that it becomes much harder to break this down without running into the same issues that have plagued weighted events systems. For instance, I wanted to do a sidebar on pitcher put-outs, because the range of abilities initially seems huge: The Royals, for instance, sit at 7%, while the Diamondbacks were at 2%. But that figure doesn’t mean all that much, because a first baseman who flips to the pitcher for the putout could swing the ranking from worst to first with 50 courteous plays over the course of the season.

What I’m more interested in is where teams are getting their outs from, particularly if that doesn’t match up with their staff tendencies. For example, is there a case of a severe ground-ball staff that’s still getting a large share of its outs from the outfielders? That would seem to indicate a particularly bad infield unit. At the same time, the range of OF PO/FB ran from 65% to 77%, the infield PO/GB ran from 100% to 115%.

Let’s go to the graph:

You can see that there aren’t any tremendous outliers. In general, the more fly balls teams induce, the more outs they get from the outfield, and vice versa. Yeah, I know, that’s not the kind of dramatic insight you wanted from this column, but this is an interesting testament to a dynamic within every team: No defensive unit, infield or outfield, is allowed to get so bad that their out production is dramatically out of whack from what you’d expect, given only the team’s ratio of ground balls to playable fly balls.

Even the Twins, who show up at the extreme of both my IF and OF PO ranges, appear here as the single set of dots to the far-left, but their infield production and lack of outfield production still puts them just off the line you’d draw through the other 29 teams.

This points to something strange. Teams, good defensively overall or bad defensively overall, are more or less equally good or bad in both their outfield and infield units. Now, whether this results from a managerial desire to balance their rosters by concentrating on using their bench to shore up the weaker unit with defensive replacements, or if it just shows us that organizations that value defense value it consistently through positions…I don’t know. Honestly, when I started this I was sure there would be a couple teams with hugely unbalanced units, and that’s all I have for possible explanations on why it’s not the case.

In any event, looking at the complexity of trying to further slice infield defense down without having play-by-play data, I’m heading back to outfield unit defense again next time.

Thank you for reading

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