Reconsidering My Player Valuation Method

Prior to the season, as part of the FanGraphs+ offering, I went over my methodology for creating ottoneu player valuations, which included my decision to use Points/PA rather than total points or points per game evaluate players in points leagues. In fact, my preference in almost all formats is to break players down to their per PA values and rank them based on how much production above replacement level they provide in that increment.

This led to a debate on the relative merits of Pts/PA vs. Pts/G, in which I basically stood by the fact that the per PA method better accounted for platoon players – guys who pinch hit a lot and therefore have a lot of low-point games thanks to getting only 1-2 PA. And while I still contend that Pts/PA is better than Pts/G, I have been wondering if there is not a third way.

In ottoneu leagues, owners are limited to a certain number of games played by position. This means that if you had started, for example, A’s 1B/OF Brandon Moss everyday, you would get 145 games played. If you only played Moss when he started, you lost 30 of those games, but you only missed out on 28 of his plate appearances. Contrast this with Cincinnati OF Jay Bruce, who played in 160 games and started them all.

Over the 2013 season, both the A’s and Reds has .327 team OBP, and Moss and Bruce both hit in (roughly) the same lineup spot (both hit 5th most often; Moss’s average lineup spot was 4.7, Bruce’s was 4.8). Based on this, you would expect both players to get roughly the same number of PA per game.

As is evident by the 28 PA in 30 games Moss added as a sub, that is not the case. In fact, Bruce managed nearly an extra PA per game – 4.36 to Moss’s 3.48. Assuming they put up the same stats per PA (they didn’t), Bruce would have been worth about 25% more per game than Moss.

Instead, by using Pts/PA, I effectively assumed these two – on similar teams in similar lineup spots – would put up roughly the same number of PA per game started. This, however, was also not accurate.

Moss started 115 games and in those 115 came to the plate 477 times, for 4.15 PA/Start. Bruce, as noted, started every game he played, so his 4.36 PA/G holds. Despite the fact that Moss hit slightly earlier in the lineup on average, he put up more than .2 fewer PA per game. This may not seem like a lot, but over the 115 games that Moss started, that works out to about 23 fewer plate appearances, or roughly five games lost. This means that Pts/PA actually overrates Moss compared to Bruce.

The reason for this is the same as the reason why Pts/G overrates Bruce – Moss’s platoon split means that he often gets pulled for pinch hitters late in the game. The same problem can occur for weak defensive players, who may lose PA to defensive replacements, or even to National League players who get pulled for a double switch.

At the end of the day, if you look only at total points (904.7 for Bruce, 728.2 for Moss) or points per game (5.65 to 5.02), Bruce looks much better. On a per PA basis (1.44 for Moss to 1.30 for Bruce), Moss appears significantly more valuable. But what really matters is what you can expect to get from each player if you use your limited resource (one game played) on them. And on a per game started basis, Moss (6.20) outshines Bruce (5.65), but by a smaller margin than on a per PA basis (note that Moss actually had a slightly better Pts/PA split as a starter than overall).

Let’s look at two fictional players, based (roughly) on Moss and Bruce. Players A and B both hit in the same spot in similar lineups. Player A plays in and starts all 162 games with 700 PA and 1000 points scored. Player B plays in all 162 games, but starts only 120, accruing 522 PA 480 as a starter) and 805 points (740.2 as a starter).

Here are their stats on per game, per PA, and per start basis:

  A B
Pts/G 6.17 4.97
Pts/PA 1.43 1.54
Pts/GS 6.17 6.17

Per game, A seems like the better bet, and if you build values based on Pts/G, you will bid more on him. On a per PA basis, B looks like the better value. In reality, you get exactly the same contribution from them for each game they start. In this case, you would bid more on Player A, as you would get his contribution in 162 games, vs. 120 games of that contribution plus 42 of a replacement level player.

Regardless, what both this example and the Bruce/Moss comparison show is the best method for valuation is likely to look at start vs. sub splits and only consider stats as a starter. My goal for this off-season is to build a spreadsheet that can consider the following equation for each player:

Players Projected Value = [(Projected Points per PA)*(PA per Game in which Said Player is a Starter)*(Games Said Player is Projected to Play)+(Replacement Level Points per PA)*(Average PA per Game Started)*(162-GAmes Said Player is Projected to Play]*(Some per Point Dollar Value)

Some of these variables are relatively easy to come across, and are closely related to what I did for 2013. But since no projection system is going to project starter vs. sub splits, I need to a) find a spreadsheet of past starter split statistics and b) figure out if it is safe to assume that a guys playing time split between will be constant moving forward.

For now, suffice it to say, neither Pts/G or Pts/PA are ideal and if you can figure out a players production on a per start basis, you are one step closer to perfecting your auction values.

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Chad Young is a product manager at Amazon by day and a baseball writer (RotoGraphs, Let's Go Tribe), sports fan and digital enthusiast at all times. Follow him on Twitter @chadyoung.

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Good stuff, Chad.

I also prefer to value players by Pts/PA but have found that one folly of doing so is the tendency to over-value injury-prone players. I got burned last year having Allen Craig, Jake Peavy, Josh Johnson, and Carlos Quentin (among others) on my roster, all of whom lost significant chunks of time (which could have been predicted based on injury history) despite top notch past/projected Pts/PA[IP].