I\'m not one to jump on the "Mel gave Stanford a spark" bandwagon. She did step up and play more than she was expected to, but
Stanford played better without Mel in the game (S 25, A&M 19) than when she was in the game (S 37, A&M 44).
Performance-based effectiveness indicates that Mel and Chiney were the least effective players, in that A&M scored more points than Stanford did while they were in the game.
I never liked simply rating players on a team by their scoring. This game showed that it is more than just getting the ball into your post who, for a while, was able to score at will. Some players score big, some get the ball into them, some block shots, some keep a player from ever even getting the ball. Some sets of players play well as a team, some sets would rarely share the ball with each other.
I also do not like statistics that don\'t take into account playing time. A statement like "She\'s improved so much this year: she scored only 4 pts/game last year and 12 pts/game this year" is almost without meaning to me unless you tell me how many minutes she was playing last year and this year.
I believe the best way to come up with a single figure that shows how well a player contributes to the team is by computing the scoring delta while that player is on the court, and normalize it by playing time.
This measure is too simple and too obvious for my being the first to use it. I just am not steeped enough in basketball to know who has used it before. While it can be used to show what player has the most impact on her team, it probably isn\'t particularly good for comparing players on different teams (at least, not any more than, say, wins, points, blocks, etc. ;-)
This table shows the playing time, the scoring delta (Stanford scoring minus Texas A&M scoring) while each player was in the game, and the delta normalized to playing a full 40 minutes.
| Player | Minutes | Delta | Delta/40min |
| Chiney | 19:40 | -5 | -10.2 |
| Kayla | 40:00 | -1 | -1.0 |
| Lindy | 10:31 | 0 | 0.0 |
| Jeanette | 39:05 | 4 | 4.1 |
| Nneka | 39:20 | -1 | -1.0 |
| Mel | 26:21 | -7 | -10.6 |
| Mikaela | 20:33 | 3 | 5.8 |
| Toni | 03:33 | 1 | 11.3 |
| Sarah | 00:57 | 1 | 42.1 |
Quote:"What? We saw the "spark" that Mel gave to the team? Why isn\'t that reflected here?"
The answer is that what you didn\'t see when Mel was in was Stanford being effective in offense for whatever reason. Maybe it was her failing to feed Nneka, or traveling, or maybe not being a 3pt threat, or whatever on the offense. On the defense, maybe it was her going in for a rebound when she should have been guarding her player. (For instance, A&M\'s final 3 was by her player whom she left.)
If you
extrapolate to a full 40 minutes from the time
when Mel was in the game (26:21, Stanford 37, A&M 44), the score would have been [highlight]Stanford 56.2, A&M 66.8.[/highlight]
If you extrapolate from the time
when Mel was NOT in the game (13:39, Stanford 25, A&M 19), the score would wind up [highlight]Stanford 73.3, A&M 55.7[/highlight].
Quote:"Ok, maybe. But why doesn\'t it distinguish between Nneka, Kayla, and Jeanette? Nneka had a great 31 points. Kayla had a somewhat ordinary game for her high standards. And Jeanette had so many turnovers."
This measure can\'t distinguish performance amongst players that play virtually the whole game, or amongst players that play very little time.
Quote:"But don\'t players during garbage time show better than they should?"
This measures a player\'s performance against the other team. Most times, when a team like Stanford has a big lead and puts in their other players, those players don\'t do well against the the other team. If at the same time, the other team also puts in their second string, then the Stanford second string probably shows up better than they really should.
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