Predicting Wins from Run Differential

In a previous post, I discussed the importance of run differential to winning ballgames. Run differential (runs scored minus runs allowed) seems to be the best indicator and predictor of win-loss records, having an extremely high correlation to total wins. The father of modern baseball stats analysis, Bill James, invented a formula based on run differential to predict a team’s winning percentage, and that percentage can help us to predict how certain teams may do down the stretch.

(That formula is simply:   (runs scored)^2 / ((runs scored)^2 + (runs allowed)^2). *The little arrows indicate that the run totals are squared.)

While some teams may just be good at winning close games, there is likely a luck factor in play with many ballclubs’ records. As we get into late summer, we can use Bill James’ formula to predict which teams are likely to pick it up in the win column or, well, not.

Don’t worry. You don’t have to do any work yourself! Baseball Reference has already done it for you. Scanning over this Baseball Reference page to the “Luck” column, we can see which teams are outperforming and under-performing their expectations. Then, a brief look over to the “1run” column shows us each team’s record in games decided by one run. It is not surprising that there is a strong correlation between one-run win-loss records and “luck factors.” Teams that win a lot of close games are generally the recipients of some good fortune – likely in combination with poise and skill – that can lead to discrepancies between the formula win percentage and the actual win percentage.

Focusing in on two particular teams, the LA Angels have a luck factor of 2  and a win-loss record of 15-9 in one-run games, while Tampa Bay is at a -5 luck factor and 9-13 in the close ones (as of 6-28-09). There are legitimate arguments that some teams are just made to win, whether by 1 run or 10, and that it’s not luck. Perhaps a good bullpen or solid team poise in the face of defeat wills certain teams to victory…a “clutch rating” if you will.

While I cannot disprove the existence of clutch in baseball, there is little to indicate that the Angels are a clutch team, or any more clutch than the Rays. On the pitching side, LA’s bullpen ERA is higher than the league average, their save and win-loss percentages are at the league average, and their relievers allow inherited runners (runners left on by the previous pitcher) to score at the league average rate. Sense a pattern? Overall, the Angels have a very much mediocre relief staff finishing off games this season.

On the offensive side, the Halos are scoring runs in the later innings at a clip just slightly worse than their own average for all innings, and below the Rays’ average. In addition, LA’s team OPS when the game is within two runs is actually slightly lower than their overall team OPS, and much lower than the Rays’ close-game OPS (.766 vs .793).

Everything points to the Angels being a medicore clutch team, yet they are 15-9 in one-run games. Why? Likely because 1-run games are like coin flips for most teams. I’m not trying to say the Angels are going to flounder – especially considering that they are getting healthier – but I am simply trying to show another way to measure luck. Since luck does not accumulate, we expect the Angels close-game winning percentage drop.

Those same Rays that have a 9-13 record in close games and a luck factor of -5 beat out the Angels in every single clutch stat mentioned above. In fact, the Rays expected record is the best in the American League. Considering there’s nothing indicating they lack “clutch,” and nothing that indicates it matters anyway, look for the Rays to nab a playoff spot in the incredibly competetive AL East.

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2 Responses to Predicting Wins from Run Differential

  1. WillB says:

    While I don’t disagree with your overall argument about run differential, I want to point out that ERA and win-loss records–both of which you use to analyze the Angels’ pen–are not good indicators of pitching strength. Stats like ERA+ or APR give a more accurate picture of the quality of a given pitcher or staff. They may well reinforce the claims you make here, so check them out if you find time.

  2. uoduckfan33 says:

    In “late and close” situations, the Angels team sOPS+ is quite a bit worse than the average. This figure measures a staff’s OPS allowed against the league average in situations defined by Baseball Reference as “plate appearances in the 7th inning or later with the batting team tied, ahead by one, or the tying run at least on deck.” Also, Angels pitching actually performs worse in terms of OPS during clutch situations than during all other situations.

    I think this OPS+ stat is fair to use since there is a strong correlation between OPS and runs scoring.

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