Looking for Clutch Performance in One-Run Games |
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You used to hear a lot (and perhaps still do) about a particular team's performance in one-run games and when you did, it was often used to either praise or damn their ability to perform in clutch situations. So I decided to look at which teams had the greatest differences between their winning percentage in games both decided and not decided by one run. Here are the teams that improved the most in one-run games: --- one-run games -- ------ others ------ Year Team G W L T Pct G W L T Pct Diff 1974 SD N 47 31 16 0 .660 115 29 86 6 .252 +.407 1955 KC A 45 30 15 0 .667 109 33 76 7 .303 +.364 1921 PHI N 45 25 20 0 .556 109 26 83 8 .239 +.317 1939 PHI N 50 25 25 0 .500 101 20 81 9 .198 +.302 1994 FLA N 36 23 13 0 .639 79 28 51 5 .354 +.284 And declined the most: --- one-run games -- ------ others ------ Year Team G W L T Pct G W L T Pct Diff 1935 NY A 44 15 29 0 .341 105 74 31 2 .705 -.364 1948 CLE A 30 10 20 0 .333 125 87 38 2 .696 -.363 1963 MIN A 39 13 26 0 .333 122 78 44 3 .639 -.306 1947 NY A 51 22 29 0 .431 103 75 28 2 .728 -.297 1935 DET A 46 19 27 0 .413 105 74 31 2 .705 -.292 So what does this mean? Is this really an indication of clutch performance? Not at all. Notice that the teams doing much better in close games are very bad teams while the ones doing worse are very good teams. My feeling is that upsets tend to be close games, and that most very good teams do their worst in one-run games, slightly better in two-run games, and so on. So rather than comparing a team's performance in one-run games to their performance in other games, perhaps we should look at how they do in those situations compared to other teams of similar ability. To do this, I divided all teams in groups by their overall winning percentage and looked at median winning percentages in games decided by 1, 2, 3, 4 and 5 runs or more. Here's what I found: Wpct Teams 1-Run 2-Run 3-Run 4-Run 5+Run < .375 149 .400 .360 .333 .316 .245 .375 - .425 212 .442 .414 .400 .400 .340 .425 - .475 338 .467 .458 .455 .444 .421 .475 - .525 386 .500 .500 .500 .500 .500 .525 - .575 417 .527 .538 .556 .556 .575 .575 - .625 255 .560 .586 .593 .611 .641 > .625 109 .600 .621 .667 .667 .733 Which, surprisingly enough, is exactly what I expected to see. So dividing the games into only two groups (one-run games and all others), we find the following median differences: Wpct Teams 1-Run Other Diff < .375 149 .400 .316 +.084 .375 - .425 210 .442 .382 +.060 .425 - .475 341 .467 .442 +.025 .475 - .525 383 .500 .500 +.000 .525 - .575 418 .527 .555 -.028 .575 - .625 256 .560 .614 -.054 > .625 109 .600 .674 -.074 After adjusting for the type of teams we're dealing with (subtracting .084 if the team has a winning percentage of less than .375, and so on), which ones did the best and worst in one-run games? Here's the updated list of the best teams: one-run games ---- others --- Year Team W L T Pct W L T Pct Diff Adj 1974 SD N 31 16 0 .660 29 86 0 .252 +.407 +.323 1955 KC A 30 15 0 .667 33 76 1 .303 +.364 +.304 1981 BAL A 21 7 0 .750 38 39 0 .494 +.256 +.284 1994 FLA N 23 13 0 .639 28 51 0 .354 +.284 +.259 1972 NY N 33 15 0 .688 50 58 0 .463 +.225 +.253 And the worst: one-run games ---- others --- Year Team W L T Pct W L T Pct Diff Adj 1966 NY A 15 38 0 .283 55 51 1 .519 -.236 -.261 1929 NY N 15 28 0 .349 69 39 1 .639 -.290 -.262 1963 MIN A 13 26 0 .333 78 44 0 .639 -.306 -.278 1948 CLE A 10 20 0 .333 87 38 1 .696 -.363 -.289 1935 NY A 15 29 0 .341 74 31 0 .705 -.364 -.310 While these lists are still biased toward very bad teams (no team that plays .705 in their other games can be expected to do much better in one-run games), at least now there are two winning teams on the "best" list and a losing team on the "worst". Still, this adjustment doesn't help to explain the variations we often see among teams of similar ability. For example, here are the best and worst one-run teams since 1901 in each of our groups: Overall one-run games ---- others --- Wpct Year Team W L T Pct W L T Pct Diff < .375 1974 SD N 31 16 0 .660 29 86 0 .252 .407 1981 SD N 12 30 0 .286 29 39 0 .426 -.141 .375 - .425 1955 KC A 30 15 0 .667 33 76 1 .303 .364 1919 WAS A 14 36 0 .280 42 48 2 .467 -.187 .425 - .475 1994 FLA N 23 13 0 .639 28 51 0 .354 .284 1966 NY A 15 38 0 .283 55 51 1 .519 -.236 .475 - .525 1959 PIT N 36 19 0 .655 42 57 1 .424 .230 1973 MIN A 12 27 0 .308 69 54 0 .561 -.253 .525 - .575 1981 BAL A 21 7 0 .750 38 39 0 .494 .256 1963 MIN A 13 26 0 .333 78 44 0 .639 -.306 .575 - .625 1913 WAS A 32 13 0 .711 58 51 1 .532 .179 1935 NY A 15 29 0 .341 74 31 0 .705 -.364 > .625 1908 PIT N 33 12 0 .733 65 44 1 .596 .137 1948 CLE A 10 20 0 .333 87 38 1 .696 -.363 What accounts for these variations within groups? Is it luck or an ability (or lack thereof) to score and prevent runs when the game is on the line? I usually groan when people start talking about clutch performance (much like the dreaded "intangibles" which, by the way, can now be accurately measured using a method I recently developed called, simply, the "Rafael-Belliard-O-Meter"), but as bad as my attitude might be on the subject, I would dearly love to be the first one on my block to show that such a talent does exist. If it isn't luck, you might expect that a penchant for winning close games would stick around from year to year. Most people agree that winning is not simply caused by good fortune, and (the Florida Marlins notwithstanding) most teams with high winning percentages one year tend to experience similar success the next. So my first attempt at proving that clutch ability is to blame for teams excelling in one-run games was to look at the variation in this area from year to year. In the chart below, "Wpct" contains information on the delta from one year to the next in a team's overall winning percentage, while "AdjD" contains similar data on the adjusted difference between a team's performance in one-run games and those decided by more than a single run. For example, if our entire database consisted of the following three years: -- Overall -- -- One-Run -- --- Others -- Year Team W L T WPct W L T WPct W L T WPct Diff AdjD* 1968 ATL N 81 81 1 .500 27 30 0 .474 54 51 1 .514 -.041 -.041 1969 ATL N 93 69 0 .574 28 17 0 .622 65 52 0 .556 .067 .095 1970 ATL N 76 86 0 .469 20 24 0 .455 56 62 0 .475 -.020 -.045 My chart would look like: --- Wpct --- --- AdjD --- Samples Avg StDev Avg StDev 2 .0895 .0155 .1380 .0020 Where: .0895 = ( ( .574 - .500 ) + ( .574 - .469 ) ) / 2 .0155 = the standard deviation of .074 and .105 .1380 ( ( .095 - -.041 ) + ( .095 - -.045 ) ) / 2 .0020 = the standard deviation of .136 and .140 Here's what the chart looks like on all teams from 1901-1997: --- Wpct --- --- AdjD --- Samples Avg StDev Avg StDev 1838 .0594 .0455 .1003 .0770 Frankly, I was surprised that a team's overall performance varied as much from year to year as it did, but that was nothing compared to the variability in its success in one-run games. Still, this doesn't by itself prove anything, since on one hand we were looking at a single percentage involving (with some exceptions) between 154-162 games, while on the other we were comparing two percentages involving around 50 and 100 games. Had I paid closer attention during my statistics course in college, I probably could've done something more with these results, but instead I decided to change the study slightly. Where before I had compared each team's record to how it did the following year, this time I compared its record to another team and year selected at random. If I'm correct and success in one-run games is merely a crap-shoot, the "Wpct" totals should jump quite a bit, but the "AdjD" totals should stay about the same. The results: --- Wpct --- --- AdjD --- Samples Avg StDev Avg StDev 1838 .0952 .0711 .1034 .0776 In other words, how a team does one year in close games is absolutely no use in predicting how it will do the next. Things like that are usually called "the breaks of the game" or, more succinctly, luck. After doing this study, I noticed an article on the same subject in the 1997 Baseball Research Journal. The article by Bob Boynton, "Are One-Run Games Special?" takes a very different route but arrives at the same conclusion that I did. Some loose ends: As you might've guessed, 1935 was a strange year in the AL for one-run decisions. Here are the standings, based on their one-run games, compared to how they actually finished the season: Team W L Pct GB Fin BOS A 28 17 .622 - 4 CLE A 22 16 .579 2.5 3 STL A 21 16 .568 3 7 CHI A 24 19 .558 3 5 PHI A 19 16 .543 4 8 WAS A 20 28 .417 9.5 6 DET A 19 27 .413 9.5 1 NY A 15 29 .341 12.5 2 In the World Series that year, Detroit won all three of their one-run games on route to a 4-2 victory over the Cubs. Go figure. A team's record in one-run games does not also seem to be a good indicator of the strength of the bullpen. For example: in 1997, the Seattle Mariners were only slightly worse (.543 vs .560) in one-run games, despite their historically awful bullpen, a smaller drop-off than the Baltimore Orioles experienced (.560 vs .625) with an excellent relief corps. By the way, here are five teams that did exactly the same in both situations: --- one-run games -- ------ others ------ Year Team G W L T* Pct G W L T Pct Diff 1902 CIN N 38 19 19 0 .500 102 51 51 5 .500 .000 1992 NY N 54 24 30 0 .444 108 48 60 5 .444 .000 1993 LA N 54 27 27 0 .500 108 54 54 4 .500 .000 1957 BAL A 54 27 27 0 .500 98 49 49 7 .500 .000 1966 CLE A 60 30 30 0 .500 102 51 51 5 .500 .000 * You might have wondered why I included a "tie" category for one-run games. After all, how can a team tie a one-run game? Well, it's happened four times, in 1937, 1938, 1939 and 1940. The last time was a 1-0 tie between the Yankees and White Sox on June 20th, 1940. These were protested games in which the statistics were kept but the loss and win were discarded. Complete DataTom Ruane |
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