(*) MASTER NOTES: Games Remaining

NOTE: A PDF version of tables relating to this piece is available. See the link at the end of this article.

Suppose you’re negotiating a deal with someone in your league. He’s accepted your part of the offer, and in return has given you the names of two OFs, from whom you can pick one. The two hitters’ skills and power/speed profiles are similar enough that there’s no clear distinction between them.

You could toss a coin, but there’s something else to consider, especially this deep into the season. That consideration comes in two parts: How many games does each player’s team have left to play? And against what teams will they be played?

Because of the regular rhythms of the schedule, it’s easy to fall into the belief that all the teams make their way through the schedule at the same pace, and roughly speaking against opponents who all even out.

In the long run—the full season—that’s mostly true, although divisional imbalances can mean some teams have a tougher go of it than others.

But in the short run, with less than a third of the season left to go, there are several imbalances in both quantity and quality that the canny owner can exploit to advantage.

Let’s start simply, with just the number of games remaining (GR). The GR table has 14 teams with 49 GR, and eight more with 48. Not much advantage there. But at the margins, there is a significant gap, especially when considering hitters.

At the high end, CLE and PIT have 51GR, BOS, CHC and MIL have 50 GR—four or five more than teams at the low end like PHI (46 GR), and TOR and TEX (47). This gap means a CLE or PIT regular hitter will 20-25 more PA, and in the short run, that’s a very useful advantage in the counting stats.

We can also break the examination down further by home and away GR. CLE leads all teams in home GR, with 30, but oddly the second-place team is TEX, second-fewest GR overall but second-most at home with 29. BOS, an overall GR leader, is tied with STL for fewest home GR, with just 20 games in their home ballparks. And TOR has the worst of both worlds, with just 47 GR, second-fewest, and only 22 at home, fourth-fewest.

So the moral of this part of the story is that all other things equal (and they seldom are), you might enjoy some PT and counting-stat dividends by targeting hitters from MIL, CHC, BOS, PIT and, especially, CLE, which also enjoys a home GR advantage.

At the same time, it could also pay to avoid players from PHI, STL, TOR and maybe TEX, keeping in mind that Rangers’ overall GR disadvantage is somewhat ameliorated by a pretty solid homeward tilt.

The other part of team value as it might affect hitters is the quality of the opposition. Again, all else equal (and it seldom is), we’d want to have hitters who get to ply their trades against teams that surrender a lot of runs.

The gamewide average R/G is around 4.40, so I looked for teams roughly 10% higher (worse) than that level or 10% lower (better). The higher/worse teams are CIN (5.46), ARI (5.44), COL (5.04), SD (4.81) and OAK (4.80), while the lower/better teams are CHC (3.36), WAS (3.49), NYM (3.61), LA (3.84) and SF (3.99).

What you want is a hitter on a team facing the most possible bad teams. The leader in that category is LA, with 24—fully half of their GR—against the sadder sacks: seven against ARI and COL, four against CIN, and six against SD. Meanwhile, they have just 12 against the good teams (including nine against rival SF) and 12 more against the neutral teams in the middle.

SF, ARI and SD have just under 20 GR apiece against bad teams, but also nearly 20 each against good teams.

KC has only 13 GR against bad teams, and none against good. Other teams with no GR vs good teams, and who therefore should be of interest, are DET, CHW, BOS, CLE, OAK, SEA, TAM, TEX and TOR. Among these, OAK has no games against bad teams, either—all 48 GR are against neutral opposition. MIN and NYY have three games each against good teams but no games against bad teams.

And ATL and CIN, already having awful seasons, get little respite from the schedule. Both teams have far more games against good teams than bad. The worst in that department is PHI, with three against bad teams and 20 against good.

Finally, I made a quick Excel sheet to figure out expected runs for and against all the teams in MLB, taking the average of the current RS/G and RA/G numbers for each team pairing, then multiplying by the number of games for an estimate of how many runs each team will score and surrender.

The full table is part of the PDF package linked at the bottom of this page, but suffice to say the top run-scoring teams track the GR totals pretty closely: BOS, CHC and CLE are the top three, NYM, ATL and PHI are the bottom.

As far as allowing runs, GR seems to have less influence than quality of team. The top three in RA/G are WAS, NYM and CHC, with the bottom three CIN, ARI and MIL.

This is a pretty big package of data to sift through and think about. If I had to summarize it into a few recommendations, and I actually do have to because the editors here do tell me to, I’d say this:

• Don’t acquire a guy just because he’s on a favorable team. Skills trump all. The idea here is to use the team connection to break ties between highly similar players.
• Don’t use the team info here to assess pitchers. Too few games, and too much performance variance in the short run.
• Target hitters on CLE, BOS and CHC. They all have extra games relative to the pack, some exposure to the poor run-prevention teams and limited exposure to good run-prevention opponents. DET hitters have 10 shots at poor teams and no good ones to worry about. KC also has a 13-0 bad-good ratio.
• Be wary of acquiring hitters on CIN, COL, PIT, SD and SF, all of which play a lot of games against the better run-preventers.

And finally, remember you can do this due diligence easily and quickly on your own. When faced with a choice between two hitters, quickly check his team’s GR and RoS schedule, and see if there’s an edge to be gained. It might be small, but at this time of year, small edges are likely to be all you’re gonna get.

Get the PDF of charts and tables accompanying this article here.

More From Archives