Comparing the tools and other traits of value of Mookie Betts and Mike Trout in 2016

Mike Trout’s AL MVP win yesterday was preceded by a lot of talk about who really was the more valuable player in 2016, Mike Trout or Mookie Betts. I’ve noticed, though, a lot of those assessments didn’t have the facts quite right. Others overlooked some things that matter. Some may look at the competing lists of WAR numbers, see that Trout is ahead of Betts on both of them, and just call it for Trout. I say there’s more to it than that. So I wrote this article to try to ensure people have the comparisons correct, and to point out what they may be overlooking.

One thing about WAR is that there are at least two versions out there (the FanGraphs version and the version), and the variances in the different versions show that WAR is not a perfectly calculated statistic. Small differences in WAR leave room for further analysis, so I think it’s worth breaking down the two players based on each of their five tools. Beyond that, I’ll look at traits that don’t factor into WAR calculations but still impact a team’s win totals (clubhouse presence) and a ballclub’s revenues (fun to watch, and likeability). Though this article is focused on who Trout and Betts were in 2016, I may reference some things that happened in earlier seasons as examples.

I’ll rate these loosely using the following categories. As a rule of thumb, these correspond approximately to the following percentiles of performance:

Average 43rd to 57th percentiles
Above average 58th to 70th percentiles
Well above average 71st to 84th percentiles
Excellent 85th to 94th percentiles
Elite Top 5%

Note that one of the tools is traditionally called “Hitting for average”. I’m updating this to “Reaching base”, as these days on-base percentage is considered more important than batting average. Another is traditionally called “speed”. I’m updating this to “baserunning”.

First the results, followed by the analysis. After looking at the 2016 numbers for both players and mixing in anecdotes and commentary I’ve come across, and actual play that I’ve witnessed, I came up with these assessments of their five tools:

Tool Trout Betts
Speed/baserunning Elite Elite
Hitting for average/on base Beyond Elite Excellent
Hitting for power Well above average Well above average
Arm strength Average Excellent
Fielding Average Elite

Looking at traits that don’t contribute to WAR but do contribute to a ballclub’s bottom line, I came up with these results:

Trait Trout Betts
Glue – clubhouse presence Above average Elite
Fun to watch Above average Elite
Likability Well above average Excellent

Let’s break these down.

Both players are elite. On stealing bases, they’re about the same; most teams would prefer to have Betts’ 26 steals versus 4 times caught stealing over Trout’s 30 steals versus 7 times caught stealing, but this really is kind of a toss up. Fangraphs’ BsR agrees. BsR puts a value in runs produced on all aspects of baserunning, including base stealing prowess, extra bases taken, outs on the bases, and avoiding double plays. Mike Trout had the fourth best BsR in 2016 among all players, at 9.3. Betts had the third best at 9.8. It’s basically a toss-up.

Hitting for power
While most probably think of Trout as more of a power hitter than Betts is, that’s not really true anymore. Per plate appearance, Trout and Betts hit home runs and triples at the exact same rates in 2016. Betts hit doubles more frequently (5.8% to Trout’s 4.7%) and singles more frequently (18.6% to 15.7%). If we divide by at bats instead of plate appearances, however, Trout’s power numbers start looking better, because we’re not including his very frequent walks and hit-by-pitches in the divisor. If we were to look at slugging percentage alone, we might give both Betts and Trout an “Excellent” for power; but when you look at stats like ISO that isolate power from on-base ability, both end up in the well-above-average range instead.

Reaching base
Trout blows Betts out of the water in walk rate, 17.0% to Betts’ 6.7%. Also Trout’s hit-by-pitch rate of 1.6% was much higher than Betts’ 0.3%. Trout’s 20.1% strikeout rate was much worse than Betts’ 11.0%, though.

So at the plate, the main difference in results is Trout’s extremely high on-base rate due to taking so many walks, and the main difference in approach is that Betts puts the ball in play a lot, and Trout does not. Only about 4% of qualifiers put the ball in play more frequently than Betts; only about 7% put the ball in play less frequently than Trout.

Trout’s .441 on base percentage led all of baseball. In the American League, it wasn’t even close. The next several players on the list were all clustered around .400. In the National League, only Joey Votto’s .434 came close. It’s obvious Trout deserves elite status in this category, but I though his separation from the pack warranted a little more, so I gave him a “beyond elite” instead.

Arm strength
There’s a component of UZR that measures arm strength not just by velocity but also accuracy. Betts qualifies as “excellent” for arm strength based on this, and based on the eye test (such as when he threw a perfectly-placed laser beam of a throw to gun down one of the game’s fastest runners, Kevin Kiermaier, trying to take third on a fly out to right). Trout actually rates below average on this, though not by a whole lot. I’m upping that to “average” based on the anectodal evidence that he’s improved his arm strength to be average or a little above average.

Some metrics have Betts as the best defender in baseball in 2016. Others have him a few notches down. But they certainly put him at an elite level, even when you remove arm strength from the equation. Trout’s fielding was actually average in 2016, even if you separate this from arm strength. This may surprise some who think of him as an above average fielder; they may have formed this impression based on his rookie season in which he was above average as a fielder. He hasn’t been better than average since, however.

Clubhouse Presence
Those are (a slightly altered version of) the so-called “five tools”. Now some may disagree, but I really do think there is a “sixth tool” a player can have to impact his team’s win total, which we can call “clubhouse presence”. It’s anything about a player that makes his teammates want to give their best effort during preparation to play and during actual gameplay. It affects win totals because, in my opinion, the results achieved on the field are a product of three things: skill, preparation, and effort, and clubhouse presence impacts two of those.

Mike Trout may or may not set a good example to his teammates by working hard on preparation. I don’t know. I do know he worked hard on his one area of weakness, his throwing arm, to eliminate the weakness. One thing I know about Mookie Betts is that he is constantly asking people questions on how to improve, and that will certainly set a tone that players can be working hard on preparation.

Trout is a positive, good-natured guy who plays Pokemon Go and Nerf basketball in the clubhouse. Certainly not a clubhouse drain. But at the same time he doesn’t seem to be very outgoing. Betts is the kind of guy who’s friends with everybody. He’s got friends on his team and on all the other teams. Having his personality in the clubhouse and on the field makes baseball fun for everyone, and that helps get maximal effort from the players on the team.

So I’m giving Trout an “above average” on clubhouse presence, but Betts an “elite”, because his type of personality is actually pretty rare.

Fun to Watch and Likability
These last two traits are all about the fans. What, aside from winning games, hitting home runs, etc. gets fans to fork over their money to watch a team play? To me, it’s being fun to watch and being likable.

Trout climbing the outfield fence to rob a home run makes him fun to watch. Mookie Betts stealing two bases on one play (with no error), or alertly taking an unmanned second base on an infield single, these are unique plays that nobody’s ever seen before, and help to make him an elite for this category. His catches on defense can be quite spectacular and acrobatic, too, such as the time he almost fell into the Fenway Park bullpen while making a game-ending, home-run robbing grab to preserve Rich Hill’s masterful shutout late in 2015. The excitement he visibly displayed while running back into the infield with the ball held high in his glove is an example of the enthusiasm for baseball that always radiates unrestrained from Betts. Oh, and who did he steal that home run from … that’s right, it was none other than Mike Trout. So I guess they kind of teamed up on that one. Trout probably had to smile at that.

Trout smiles a lot. So does Betts. But I’d say that Betts is the one with the “winning” smile. Electric. Unrestrained. Wins you over, and wins fans over. They’re both likable, but Betts is in a higher category of likable.

So there you have it. Looking over these ratings, Betts is one of the best in the game in every category except hitting for power, and he’s approaching being one of the best in that, too. He’s pretty much everything you could want in a player. Trout is definitely better at the plate, which is the most important part of achieving a high WAR. But his “secret weapon” has been his excellent baserunning, and Betts is his match there. In every other aspect of the game, the fielding aspects and also the less tangible but still valuable ones, Betts is his superior.

I’m not concluding that Betts should have gotten the MVP over Trout. But there’s been a lot of debate on that topic, and there may be some yet to come. But it seems to me that a lot of people have wrong ideas on how close Betts and Trout are on baserunning and power hitting, and many overestimate Trout’s fielding ability. There also never seems to be discussion of clubhouse presence, likability, and being fun to watch, and those do carry value. I wrote this to help ensure that discussion doesn’t miss any of these points.

I hope to hear some good discussion on this now!


Cubs have them right where they want them

Obviously, a World Series Game 1 win would have been better for the Cubs. But when you think about the most likely scenarios in which the Cubs win the World Series, the two most likely both have the Cubs losing Game 1.

One scenario is the Cubs win all the games in which Corey Kluber doesn’t pitch, taking the Series in 6 games. But if you don’t have a midgame lead in Game 6, you’ll be facing a rested Andrew Miller in that game, not what you want.

The other scenario is the Cubs take one of the first two in Cleveland, and win all three home games. In this scenario, the most likely outcome is losing Game 1 (because Kluber is pitching) and winning Game 2.

So what sets you up best for winning Game 2? Making sure Andrew Miller throws a lot of pitches in Game 1. And hope that Game 2 isn’t rescheduled due to rain.

The Cubs definitely accomplished the first part of that. Miller threw 46 pitches in Game 1, more than he’s thrown all season. Plus, they mounted a real scoring threat against him. If they see him in Game 2, they won’t see much of him, and they won’t be intimidated by him. And he may not be as effective, either. The Cubs will be ready to succeed against Miller in Game 2, if they have to.

As for winning Game 4 against Kluber, it will help that they’re at home in Chicago. It will also help that they’d seen a lot of pitches from Kluber just four days before, so they have a better idea what to expect from him. There was some good contact against him in Game 1. They just need a little bit more good contact to start putting up runs.

For the Cubs’ sake, let’s just hope the rain doesn’t cancel Game 2.

Silver linings: despite losses, Eduardo Rodriguez still helping Red Sox win in September

Eduardo Rodriguez hasn’t earned a win in his last 9 starts, going back to mid-July. In that time, he’s had a good share of tough-luck losses and no decisions, none worse than September 4 against Oakland. Spinning a no-hitter through 7 and 2/3 innings, he finished having thrown 8 innings of shutout ball, the best start of his career. However, the Red Sox gave him exactly zero runs of support that day. This, the day after the Red Sox had scored 11 runs against the same team, and 16 the day before that. They would go on to lose 1-0.

And yet, it was not all for naught, because Rodriguez and the rest of the Red Sox starters strung together one excellent start after another to start September. By going deep into games, fewer innings were required of the relievers. By limiting runs allowed to at most 2 through the first seven games of September, the starters usually left the game with a big lead, allowing the Red Sox to pick and choose which relievers to use based on who was most rested, or who needed confidence-boosting. Some additional rest was already expected for the bullpen once rosters expanded September 1, but combined with the help from the starters, it was a perfect recipe for turning an overworked bullpen into a very well rested one.

The dividends from this rest were reaped Sunday night, as the bullpen was called on to take over at the start of the 4th inning of a close game against a potent offense and division rival in a tight pennant race. And they came through.

Let’s look at the numbers to see if they back all this up.

First, here are the performances of the Red Sox starters through the first 8 games of September:

First 8 starts of September 2016
Date Starting pitcher IP H R ER
9/2/2016 David Price 7 4 2 2
9/3/2016 Rick Porcello 7 4 2 2
9/4/2016 Eduardo Rodriguez 8 1 0 0
9/5/2016 Drew Pomeranz 5.2 6 2 2
9/6/2016 Clay Buchholz 6.2 8 1 1
9/7/2016 David Price 7 6 2 2
9/9/2016 Rick Porcello 7 6 2 2
9/10/2016 Eduardo Rodriguez 6 4 3 2

Indeed, on the whole they went quite deep into games, and allowed very few runs.  This allowed the Red Sox to use the bullpen as a whole much less:

Per game usage averages
IP (starters) IP (relievers) Pitches (rel.)
August 6.30 2.49 44.3
Sept (thru 9/10) 6.79 1.83 28.6

The bullpen as a whole threw about 1/3 fewer pitches per game through the first part of September versus their August average.  That’s a big reduction in workload.  Factor in the expanded rosters, allowing three additional relievers to be used in early September (Koji Uehara, Joe Kelly, and Robby Scott), and the usage per reliever went down.  Here are the number of appearances made per team game played in the month for each reliever.  Only pitchers making relief appearances in both months are included.

Appearances per team game though Sept 10
Aug App/G Sep App/G
Brad Ziegler 0.367 0.250
Craig Kimbrel 0.367 0.250
Fernando Abad 0.400 0.250
Heath Hembree 0.100 0.125
Junichi Tazawa 0.333 0.125
Matt Barnes 0.433 0.250
Robbie Ross 0.400 0.125

Except for Heath Hembree, who hadn’t been used much in August, the frequecy with which each reliever was called upon dropped by a third or more, for everybody.  Rest for the weary!

Better yet, thanks to improved performances by these relievers, they became more pitch-efficient.  With the exception of Brad Ziegler, the number of pitches thrown per game played by the team (not per game the pitcher participated in) dropped for each pitcher to between one sixth and one third of their previous August numbers.  That’s a lot of rest!

Pitches per team game though Sept 10
Aug Pit/G Sep Pit/G
Brad Ziegler 5.73 4.00
Craig Kimbrel 6.87 1.25
Fernando Abad 6.27 1.88
Heath Hembree 1.77 0.63
Junichi Tazawa 6.47 1.88
Matt Barnes 7.13 2.25
Robbie Ross 6.47 1.13

The performances got better, too.  Per batter faced, the frequency of undesirable results went down, and the frequency of desirable results went up:

Results per batter faced by relievers
August 22.1% 11.2% 24.8% 2.7%
Sept (thru 9/10) 18.6% 3.4% 33.9% 0.0%

Most importantly, the relievers’ overall earned run average went from poor to perfect:

Relievers’ ERA
August 4.70
Sept (thru 9/10) 0.00

Obviously, Sunday’s game threw off these low usage numbers. But that wasn’t such a bad thing, when you realize that none of these “previously overused” relievers had been called on more than twice over the previous 10 days.  They’ll need to pitch occasionally, and pitch in some pressure situations occasionally, to stay sharp.  With Uehara and Kelly back and throwing well, the Red Sox bullpen is suddenly looking like a strength.

The one thing remaining that the Red Sox have lacked is late-inning offense, especially in close games.  If they can turn that around, they’ll have all facets of their game working well.  That will make for an easy September, and an easy September will allow them to set themselves up to perform well in the playoffs.

Yes, there really is a surge in talented young baseball players now

Seems like the last 3 or 4 years there have been a lot of very excellent, very young baseball players in the major leagues.

Seems like, in that time, there has been a lot of talk about all the very excellent young baseball players in the majors, with Mike Trout and Bryce Harper leading the way. But our impressions are sometimes wrong, as analysis of the relevant data can reveal. So, to see if these impressions are right or wrong, I looked at the data.

The data agree, overwhelmingly.

Using, I looked at the highest-WAR seasons for players 22 and under from the last 40 years. Though rather than using WAR numbers outright, I scaled WAR to 150 games, to adjust for differences in playing time.  Because WAR behaves more like a cumulative statistic, like hits, than a rate statistic, like batting average, this effectively converts it to a rate statistic.  Because rate statistics are untrustworthy over small sample sizes, I only looked at seasons in which the player played in most of the games, so, at least 82 games.

Here are the top 40 such seasons from the last 40 years:

Year Player Lg Tm Age G WAR WAR/150
2012 Mike Trout AL LAA 20 139 10.8 11.7
2015 Bryce Harper NL WSN 22 153 9.9 9.7
1996 Alex Rodriguez AL SEA 20 146 9.4 9.7
1981 Rickey Henderson AL OAK 22 108 6.6 9.2
2013 Mike Trout AL LAA 21 157 8.9 8.5
1980 Rickey Henderson AL OAK 21 158 8.8 8.4
1998 Alex Rodriguez AL SEA 22 161 8.5 7.9
1983 Cal Ripken AL BAL 22 162 8.2 7.6
2014 Mike Trout AL LAA 22 157 7.9 7.5
2013 Yasiel Puig NL LAD 22 104 4.9 7.1
1998 Andruw Jones NL ATL 21 159 7.4 7.0
2015 Francisco Lindor AL CLE 21 99 4.6 7.0
1991 Ken Griffey AL SEA 21 154 7.1 6.9
2010 Jason Heyward NL ATL 20 142 6.4 6.8
2003 Hank Blalock AL TEX 22 143 6.4 6.7
2012 Giancarlo Stanton NL MIA 22 123 5.5 6.7
1982 Tom Brunansky AL MIN 21 127 5.6 6.6
2007 Troy Tulowitzki NL COL 22 155 6.8 6.6
2015 Manny Machado AL BAL 22 162 7.1 6.6
1999 Andruw Jones NL ATL 22 162 7.1 6.6
2005 Grady Sizemore AL CLE 22 158 6.6 6.3
2015 Carlos Correa AL HOU 20 99 4.1 6.2
2015 Mookie Betts AL BOS 22 145 6 6.2
2013 Manny Machado AL BAL 20 156 6.4 6.2
2001 Albert Pujols NL STL 21 161 6.6 6.1
1992 Ken Griffey AL SEA 22 142 5.8 6.1
1979 Paul Molitor AL MIL 22 140 5.6 6.0
1976 Willie Randolph AL NYY 21 125 5 6.0
1981 Tim Raines NL MON 21 88 3.5 6.0
1997 Alex Rodriguez AL SEA 21 141 5.6 6.0
1978 Robin Yount AL MIL 22 127 5 5.9
2008 Evan Longoria AL TBR 22 122 4.8 5.9
1987 Barry Bonds NL PIT 22 150 5.8 5.8
1977 Chet Lemon AL CHW 22 150 5.8 5.8
2002 Austin Kearns NL CIN 22 107 4.1 5.7
1978 Jack Clark NL SFG 22 156 5.9 5.7
2012 Jason Heyward NL ATL 22 158 5.8 5.5
2012 Bryce Harper NL WSN 19 139 5.1 5.5
2012 Brett Lawrie AL TOR 22 125 4.5 5.4
1979 Lou Whitaker AL DET 22 127 4.5 5.3

I then grouped these into 10 groups of 4 years. As it turns out, the period from 2012 to 2015 contains 5 of the top 10, 8 of the top 20, and 14 of the top 40 of these seasons, as shown by these charts. This, when the average group has 1 in the top 10, 2 in the top 20, and 4 in the top 40.

When the top 20 WAR seasons under 23 over last 40 years occurred

When the top 40 WAR seasons under 23 over last 40 years occurred

Of course, sometimes a single player produced more than one of these seasons. But these past four years also dominate in terms of the number of different young players on these lists. Here are all the players having top 40 seasons, listed under their 4-year groups, with their overall placements on the list next to their names. I’ve bolded those with top-20 seasons.

1976 – 1979 1980 – 1983 1984 – 1987
Paul Molitor (27) Rickey Henderson (4, 6) Barry Bonds (33)
Willie Randolph (28) Cal Ripken (8)
Robin Yount (31) Tom Brunansky (17)
Chet Lemon (34) Tim Raines (29)
Jack Clark (36)
Lou Whitaker (40)
1988 – 1991 1992 – 1995 1996 – 1999
Ken Griffey (13) Ken Griffey (26) Alex Rodriguez (3, 7, 30)
Andruw Jones (11, 20)
2000 – 2003 2004 – 2007 2008 – 2011
Hank Blalock (15) Troy Tulowitzki (18) Jason Heyward (14)
Albert Pujols (25) Grady Sizemore (21) Evan Longoria (32)
Austin Kearns (35)
2012 – 2015
Mike Trout (1, 5, 9)
Bryce Harper (2, 38)
Yasiel Puig (10)
Francisco Lindor (12)
Giancarlo Stanton (16)
Manny Machado (19, 24)
Carlos Correa (22)
Mookie Betts (23)
Jason Heyward (37)
Brett Lawrie (39)

Again, these past 4 years dominate.

Now that we know for certain that we’re experiencing a very special surge of young talent, the next thing to ask is, why? Has the surge in the amount of free analysis available (on the web and in ESPN in-depth commentary) over the last decade or so allowed parents to self-coach their youngsters more effectively? And is this finally coming to fruition? Or is this just a fluke? Is it a Cuban invasion? Or something else?

Xander Bogaerts back on pace to reach 200 hits, win AL batting title

Back on Wednesday morning, I showed that Xander Bogaerts and Miguel Cabrera were hitting at paces that would cause Bogaerts to (most likely) surpass Cabrera for the AL batting title. Though I didn’t mention it at the time, these projections also showed that he’d reach 200 hits even if he sat out a couple of games, and a few more than that if he played all the remaining games. After a pair of low-hit games knocked Bogaerts off that pace, his 3-for-4 performance last night has put him right back on it.

In trying to project future totals using “the pace at which a player is producing right now”, how many games do you use to determine what that pace is? The last 5? The last 10? 20?

I circumvent that question by using all of them … I calculate his pace of production over his last 5, 6, 7, 8, etc. games, then use that pace applied over the remaining number of games to be played to see what final numbers he’s headed for. This gives a big collection of possible final numbers; you then choose one in the middle.

On Wednesday I did that for Cabrera and Bogaerts using their paces of production as established by their last 8, 9, 10, etc. up to their last 20 games. That gave 13 paces of production for each player. I then applied these to their remaining games assuming they’d not sit out any games, and then again assuming they’d each sit out two games. I got these results:

If playing all remaining games
Bogaerts Cabrera
Low 0.327 0.324
Median 0.329 0.326
High 0.332 0.331
If sitting out two games
Bogaerts Cabrera
Low 0.327 0.326
Median 0.329 0.328
High 0.331 0.332

In all but one of these 26 projections, Bogaerts would end up with at least 200 hits.

I just updated these numbers, and now they look like this:

If playing all remaining games
Bogaerts Cabrera
Low 0.327 0.325
Median 0.329 0.326
High 0.330 0.332
If sitting out two games
Bogaerts Cabrera
Low 0.327 0.327
Median 0.328 0.328
High 0.329 0.332

Here are Bogaerts’ projected numbers of hits:

Bogaerts projected 2015 hits
# of recent games used If playing all games If sitting two games
20 204.0 200.8
19 203.3 200.2
18 203.0 200.0
17 203.3 200.2
16 203.6 200.5
15 204.0 200.8
14 205.1 201.7
13 204.9 201.5
12 203.8 200.7
11 204.4 201.1
10 204.0 200.8
9 204.7 201.3
8 204.3 201.0

Longer term projections (based on his last 40 or more games) almost all have him finishing with 200 hits exactly if he sits out 2 games, 203 hits if he plays all remaining games, and a .327 average.

If they play it out, and stay on pace, Bogaerts probably will win the batting title and will get to 200 hits.

Thanks to for the gamelog data I used for this article.

Xander Bogaerts on pace to surpass Miguel Cabrera for batting title

I’m a little frustrated with this article. I don’t think it gets me any closer to knowing how much of a shot Xander Bogaerts has at 2015 American League batting title. It just says, “it will be difficult”.

So I did some projections, to see what the numbers say. Of course, things have changed a bit since this article was published – the gap is now just 12 points instead of 18. There are 11 games left on the Tigers’ schedule, and 12 games left on the Red Sox’. I did two sets of projections. One assumes each player plays in all his team’s remaining games. The other assumes each player sits out two games.

In each case, I used the numbers of at bats and hits of each player in his last 8, 9, 10, etc. games, up to his last 20 games, as the basis for projecting his number of at bats and hits to come in his remaining games. I scaled these samples to the number of remaining games, added them to the current season totals, and calculated batting averages. So that made for 13 separate projections in each case.  The results:

Bogaerts projected 2015 AVG
# of recent games used If playing all games If sitting two games
20 0.330 0.329
19 0.329 0.329
18 0.330 0.329
17 0.329 0.328
16 0.328 0.327
15 0.327 0.327
14 0.328 0.327
13 0.328 0.328
12 0.330 0.329
11 0.332 0.331
10 0.331 0.330
9 0.329 0.328
8 0.330 0.329
Cabrera projected 2015 AVG
# of recent games used If playing all games If sitting two games
20 0.328 0.329
19 0.327 0.328
18 0.326 0.328
17 0.324 0.326
16 0.324 0.326
15 0.325 0.327
14 0.326 0.328
13 0.328 0.329
12 0.326 0.328
11 0.324 0.326
10 0.325 0.327
9 0.327 0.329
8 0.331 0.332

In both cases, because Bogaerts is hitting well right now and Cabrera is hitting poorly, the projections show that Bogaerts will probably surpass Cabrera and win the batting title. The charts pictured below show the lowest, highest, and median projections among the 13 projections produced for each case.

If playing all remaining games
Bogaerts Cabrera
Low 0.327 0.324
Median 0.329 0.326
High 0.332 0.331
If sitting out two games
Bogaerts Cabrera
Low 0.327 0.326
Median 0.329 0.328
High 0.331 0.332

If both players hit at their current paces the rest of the way, Xander Bogaerts will surpass Miguel Cabrera for the 2015 AL batting title.

Who should AL Player of the Month be, Encarnacion or Bradley?

To think about who should be the American League player of the Month for August, we could start by looking at those with the highest OPS on the month (and at least 50 plate appearances):

 Encarnacion, E TOR 1B 23 86 23 35 11 0 11 35 9 15 0 0 0.407 0.460 0.919 1.379
 Ortiz, D BOS DH 26 91 17 32 8 0 9 22 16 17 0 0 0.352 0.432 0.736 1.169
 Bradley, J BOS CF 26 79 23 28 9 3 5 23 11 24 3 0 0.354 0.429 0.734 1.163
 Donaldson, J TOR 3B 27 105 29 34 7 1 11 35 16 25 2 0 0.324 0.408 0.724 1.132
 Gutierrez, F SEA LF 19 62 12 21 4 0 7 20 4 19 0 0 0.339 0.388 0.742 1.130

Based on offense alone, you have to pick Encarnacion, though Ortiz, Bradley, and Donaldson all show very well here. But can defense close the gap? Not for Ortiz, the DH, but maybe for Jackie Bradley Jr., the defensive wiz in the outfield. Now I haven’t seen Encarnacion’s defense this month, but I have to wonder, how likely is he to have made plays at first base in August like this catch:

Bradley Jr.’s incredible catch

or this catch:

Statcast: Bradley’s great grab

or this throw:

Statcast: Bradley Jr. gets Bird

or this catch:

Must C: Bradley Jr.’s great grab

or this throw:

Bradley Jr. nabs Sanchez

or this catch:

Bradley runs in for catch

or this throw:

Bradley Jr.’s throw nabs Infante

or this catch and throw:

Bradley’s running catch

Given the game-changing, run-saving nature of Bradley’s defense so many times in August, that has to propel him squarely into a two-person discussion for who should be AL player of the Month for August.

Do you think the pick should be Encarnacion, Bradley, or someone else?

Red Sox almost accomplish unusual feat

Over their last four games, the Boston Red Sox have posted scores of 15, 22, 8, and 2.  Had it not been for a late rally last night, they would have finished the last of these games with just one run instead of two, and this would have made for what must be an uncommon if not unprecedented oddity.  They’d have had four consecutive different scores, each one exactly 7 runs apart from the closest of the other scores.

What they did accomplish is probably also quite rare: four consecutive games in which no two scores are within 6 runs of each other. To see if any other team has ever accomplished this feat, I might look through’s play index for games with 18 runs scored or more and then look through game logs to see the scores of the adjacent games, but with over 300 results to look through, that’s more work than I can finish on my lunch break.  So I leave it to you, baseball community:  can you find any team that has done this before?

Closure for Lester (he finally gets a hit)

As the season opened I reported on Jon Lester’s potential to break the record for most hitless at bats to start a career this season, now that he’s batting regularly as a National League pitcher.  Later, I reported on his breaking that record.  Now, at last, there is closure.  On Monday Jon Lester got his first career hit, and it was off former teammate John Lackey (literally – it ricocheted off Lackey).  He tallied 30 AB and 30 plate appearances this season before getting that hit, adding to his prior career totals of 43 PA and 36 AB without a hit.

Here is the new top 10 list:

Name Team(s) Pos PA AB First hitless game Last hitless game Hitless Games RBI SO BB HBP SH SF
Jon Lester BOS-OAK P 73 66 6/16/2006 7/1/2015 30 1 37 1 0 5 1
Joey Hamilton SDP P 66 57 5/24/1994 6/3/1995 24 1 34 2 0 6 1
Ron Herbel SFG P 63 55 5/6/1964 5/11/1965 27 0 36 2 0 6 0
Marv Breuer NYY P 57 to 60 47 to 49 4/27/1940 9/4/1940 20 1 22 or 23 4 or 5 0 6
Luke Walker PIT P 56 48 4/18/1966 4/18/1970 27 2 29 2 0 6 0
Don Carman PHI P 53 48 9/13/1984 5/11/1987 28 0 21 0 0 5 0
Fred Gladding DET-HOU P 49 47 7/1/1961 7/5/1969 40 0 27 0 0 2 0
Chris Short PHI P 45 44 4/19/1959 6/24/1961 26 0 19 0 0 1 0
Randy Tate NYM P 47 41 4/14/1975 9/18/1975 23 0 22 1 0 5 0
Pat Jarvis ATL P 45 41 8/13/1966 6/12/1967 18 1 24 2 0 2 0

Congratulations, Jon. You’ve hit some balls pretty hard to this point in your career, and streak records like this one always involve some luck, either bad or good. Now forget about hitting, because you’ve got more important concerns.